From 54191545ab62ab13141149db4d9a1c25bcaa7a28 Mon Sep 17 00:00:00 2001 From: iamwales Date: Thu, 23 Apr 2026 23:26:51 +0100 Subject: [PATCH 1/6] design updates on homepage --- .gitignore | 1 + frontend/package-lock.json | 1 + frontend/package.json | 1 + .../[id]/application-detail-page.tsx | 188 +++++++++++++++++ .../src/app/(app)/applications/[id]/page.tsx | 192 +----------------- frontend/src/app/(app)/applications/page.tsx | 2 +- frontend/src/app/(app)/apply/page.tsx | 4 +- frontend/src/app/(app)/resume/[id]/page.tsx | 74 +------ .../(app)/resume/[id]/resume-detail-page.tsx | 71 +++++++ .../(auth)/sign-in/[[...sign-in]]/page.tsx | 24 +-- .../sign-in/[[...sign-in]]/sign-in-view.tsx | 44 ++++ .../(auth)/sign-up/[[...sign-up]]/page.tsx | 24 +-- .../sign-up/[[...sign-up]]/sign-up-view.tsx | 47 +++++ frontend/src/app/globals.css | 159 +++++++++++---- frontend/src/app/layout.tsx | 59 +++--- frontend/src/app/onboarding/page.tsx | 6 +- frontend/src/app/page.tsx | 62 ++---- frontend/src/components/app-shell.tsx | 142 ++++++------- frontend/src/components/clerk-provider.tsx | 30 +++ frontend/src/components/landing-cta.tsx | 44 ---- frontend/src/components/landing-features.tsx | 133 ------------ frontend/src/components/landing-footer.tsx | 38 ---- frontend/src/components/landing-hero.tsx | 97 --------- .../src/components/landing-nav-buttons.tsx | 32 --- .../components/landing-problem-solution.tsx | 60 ------ frontend/src/components/landing-stats.tsx | 25 --- .../src/components/landing-testimonials.tsx | 69 ------- frontend/src/components/landing/CTA.tsx | 42 ++++ .../src/components/landing/FeatureItem.tsx | 21 ++ frontend/src/components/landing/Features.tsx | 72 +++++++ frontend/src/components/landing/Footer.tsx | 43 ++++ frontend/src/components/landing/Hero.tsx | 106 ++++++++++ .../src/components/landing/HeroMockup.tsx | 120 +++++++++++ .../src/components/landing/HowItWorks.tsx | 57 ++++++ .../components/landing/LandingCtaButton.tsx | 42 ++++ frontend/src/components/landing/LogoBar.tsx | 21 ++ frontend/src/components/landing/Navbar.tsx | 70 +++++++ .../src/components/landing/OutputPreview.tsx | 74 +++++++ frontend/src/components/landing/Outputs.tsx | 85 ++++++++ frontend/src/components/landing/Pricing.tsx | 68 +++++++ .../src/components/landing/PricingCard.tsx | 107 ++++++++++ frontend/src/components/landing/Stats.tsx | 30 +++ frontend/src/components/landing/StepCard.tsx | 46 +++++ frontend/src/components/match-badge.tsx | 4 +- frontend/src/components/status-badge.tsx | 8 +- frontend/src/components/ui/badge.tsx | 60 +++--- frontend/src/components/ui/button.tsx | 86 ++++---- frontend/src/components/ui/card.tsx | 93 ++++----- frontend/src/components/ui/logo-mark.tsx | 39 ++++ frontend/src/components/ui/section-header.tsx | 61 ++++++ frontend/src/lib/api.ts | 19 +- frontend/src/lib/hooks/use-api.ts | 2 +- frontend/src/lib/mock-data.ts | 1 + frontend/tsconfig.json | 1 + 54 files changed, 1914 insertions(+), 1093 deletions(-) create mode 100644 frontend/src/app/(app)/applications/[id]/application-detail-page.tsx create mode 100644 frontend/src/app/(app)/resume/[id]/resume-detail-page.tsx create mode 100644 frontend/src/app/(auth)/sign-in/[[...sign-in]]/sign-in-view.tsx create mode 100644 frontend/src/app/(auth)/sign-up/[[...sign-up]]/sign-up-view.tsx create mode 100644 frontend/src/components/clerk-provider.tsx delete mode 100644 frontend/src/components/landing-cta.tsx delete mode 100644 frontend/src/components/landing-features.tsx delete mode 100644 frontend/src/components/landing-footer.tsx delete mode 100644 frontend/src/components/landing-hero.tsx delete mode 100644 frontend/src/components/landing-nav-buttons.tsx delete mode 100644 frontend/src/components/landing-problem-solution.tsx delete mode 100644 frontend/src/components/landing-stats.tsx delete mode 100644 frontend/src/components/landing-testimonials.tsx create mode 100644 frontend/src/components/landing/CTA.tsx create mode 100644 frontend/src/components/landing/FeatureItem.tsx create mode 100644 frontend/src/components/landing/Features.tsx create mode 100644 frontend/src/components/landing/Footer.tsx create mode 100644 frontend/src/components/landing/Hero.tsx create mode 100644 frontend/src/components/landing/HeroMockup.tsx create mode 100644 frontend/src/components/landing/HowItWorks.tsx create mode 100644 frontend/src/components/landing/LandingCtaButton.tsx create mode 100644 frontend/src/components/landing/LogoBar.tsx create mode 100644 frontend/src/components/landing/Navbar.tsx create mode 100644 frontend/src/components/landing/OutputPreview.tsx create mode 100644 frontend/src/components/landing/Outputs.tsx create mode 100644 frontend/src/components/landing/Pricing.tsx create mode 100644 frontend/src/components/landing/PricingCard.tsx create mode 100644 frontend/src/components/landing/Stats.tsx create mode 100644 frontend/src/components/landing/StepCard.tsx create mode 100644 frontend/src/components/ui/logo-mark.tsx create mode 100644 frontend/src/components/ui/section-header.tsx diff --git a/.gitignore b/.gitignore index 92fbe26..26c99d9 100644 --- a/.gitignore +++ b/.gitignore @@ -58,3 +58,4 @@ terraform.rc coverage/ htmlcov/ .coverage +.cursor \ No newline at end of file diff --git a/frontend/package-lock.json b/frontend/package-lock.json index 28690ab..d70bc87 100644 --- a/frontend/package-lock.json +++ b/frontend/package-lock.json @@ -9,6 +9,7 @@ "version": "0.1.0", "dependencies": { "@clerk/nextjs": "^7.2.5", + "@clerk/react": "^6.4.3", "@radix-ui/react-dialog": "^1.1.4", "@radix-ui/react-dropdown-menu": "^2.1.6", "@radix-ui/react-label": "^2.1.2", diff --git a/frontend/package.json b/frontend/package.json index 06e0ab0..2b24360 100644 --- a/frontend/package.json +++ b/frontend/package.json @@ -10,6 +10,7 @@ }, "dependencies": { "@clerk/nextjs": "^7.2.5", + "@clerk/react": "^6.4.3", "@radix-ui/react-dialog": "^1.1.4", "@radix-ui/react-dropdown-menu": "^2.1.6", "@radix-ui/react-label": "^2.1.2", diff --git a/frontend/src/app/(app)/applications/[id]/application-detail-page.tsx b/frontend/src/app/(app)/applications/[id]/application-detail-page.tsx new file mode 100644 index 0000000..e339271 --- /dev/null +++ b/frontend/src/app/(app)/applications/[id]/application-detail-page.tsx @@ -0,0 +1,188 @@ +"use client"; + +import Link from "next/link"; +import { useParams } from "next/navigation"; +import { ArrowLeft, Download } from "lucide-react"; + +import { MatchBadge } from "@/components/match-badge"; +import { StatusBadge } from "@/components/status-badge"; +import { Button } from "@/components/ui/button"; +import { + Card, + CardContent, + CardHeader, + CardTitle, +} from "@/components/ui/card"; +import { Skeleton } from "@/components/ui/skeleton"; +import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"; +import { useApplication, useResume } from "@/lib/hooks/use-api"; + +export default function ApplicationDetailPage() { + const params = useParams<{ id: string }>(); + const id = params?.id; + + const { data: application, isLoading } = useApplication(id); + const { data: resume } = useResume(application?.resumeId); + + if (isLoading) { + return ( +
+ + +
+ ); + } + + if (!application) { + return ( +
+

Application not found.

+ +
+ ); + } + + return ( +
+
+ +
+ +
+
+

+ {application.position} +

+

{application.company}

+ {application.jobUrl ? ( + + View original posting + + ) : null} +
+
+ + +
+
+ + + + Job description + Tailored resume + Cover letter + Gap analysis + + + + + + Job description + + + 
+                {application.jobDescription}
+
+ + + + + + + + Tailored resume + {resume ? ( + + ) : null} + + + {resume ? ( + 
+                  {resume.content}
+
+ ) : ( +

+ No tailored resume yet. +

+ )} + + + + + + + + Cover letter + {application.coverLetter ? ( + + ) : null} + + + {application.coverLetter ? ( + 
+                  {application.coverLetter}
+
+ ) : ( +

+ No cover letter generated yet. +

+ )} + + + + + + + + Gap analysis + + + {(application.gaps ?? []).length === 0 ? ( +

+ No gaps detected — your profile aligns well with this role. +

+ ) : ( + (application.gaps ?? []).map((gap) => ( +
+
+

{gap.skill}

+ {gap.note ? ( +

+ {gap.note} +

+ ) : null} +
+ + {gap.severity} + +
+ )) + )} + + + + +
+ ); +} diff --git a/frontend/src/app/(app)/applications/[id]/page.tsx b/frontend/src/app/(app)/applications/[id]/page.tsx index e339271..997a4ce 100644 --- a/frontend/src/app/(app)/applications/[id]/page.tsx +++ b/frontend/src/app/(app)/applications/[id]/page.tsx @@ -1,188 +1,12 @@ -"use client"; +import ApplicationDetailPage from "./application-detail-page"; -import Link from "next/link"; -import { useParams } from "next/navigation"; -import { ArrowLeft, Download } from "lucide-react"; +/** `output: "export"`: allow dynamic segment without pre-built paths (see next/dist/build revalidate check). */ +export const revalidate = 0; -import { MatchBadge } from "@/components/match-badge"; -import { StatusBadge } from "@/components/status-badge"; -import { Button } from "@/components/ui/button"; -import { - Card, - CardContent, - CardHeader, - CardTitle, -} from "@/components/ui/card"; -import { Skeleton } from "@/components/ui/skeleton"; -import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"; -import { useApplication, useResume } from "@/lib/hooks/use-api"; - -export default function ApplicationDetailPage() { - const params = useParams<{ id: string }>(); - const id = params?.id; - - const { data: application, isLoading } = useApplication(id); - const { data: resume } = useResume(application?.resumeId); - - if (isLoading) { - return ( -
- - -
- ); - } - - if (!application) { - return ( -
-

Application not found.

- -
- ); - } - - return ( -
-
- -
- -
-
-

- {application.position} -

-

{application.company}

- {application.jobUrl ? ( - - View original posting - - ) : null} -
-
- - -
-
- - - - Job description - Tailored resume - Cover letter - Gap analysis - - - - - - Job description - - - 
-                {application.jobDescription}
-
- - - - - - - - Tailored resume - {resume ? ( - - ) : null} - - - {resume ? ( - 
-                  {resume.content}
-
- ) : ( -

- No tailored resume yet. -

- )} - - - - - - - - Cover letter - {application.coverLetter ? ( - - ) : null} - - - {application.coverLetter ? ( - 
-                  {application.coverLetter}
-
- ) : ( -

- No cover letter generated yet. -

- )} - - - +export function generateStaticParams() { + return [] as { id: string }[]; +} - - - - Gap analysis - - - {(application.gaps ?? []).length === 0 ? ( -

- No gaps detected — your profile aligns well with this role. -

- ) : ( - (application.gaps ?? []).map((gap) => ( -
-
-

{gap.skill}

- {gap.note ? ( -

- {gap.note} -

- ) : null} -
- - {gap.severity} - -
- )) - )} - - - - -
- ); +export default function ApplicationByIdPage() { + return ; } diff --git a/frontend/src/app/(app)/applications/page.tsx b/frontend/src/app/(app)/applications/page.tsx index 75d1c41..50f2287 100644 --- a/frontend/src/app/(app)/applications/page.tsx +++ b/frontend/src/app/(app)/applications/page.tsx @@ -19,7 +19,7 @@ export default function ApplicationsPage() {

Applications

- Track every job you've tailored an application for. + Track every job you've tailored an application for.

- - ); - } - - return ( -
- +export function generateStaticParams() { + return [] as { id: string }[]; +} - - -
- {resume.title} -

- Created {new Date(resume.createdAt).toLocaleDateString()} -

-
-
- {resume.isBase ? Base : null} - -
- - - 
-            {resume.content}
-
- - -
- ); +export default function ResumeByIdPage() { + return ; } diff --git a/frontend/src/app/(app)/resume/[id]/resume-detail-page.tsx b/frontend/src/app/(app)/resume/[id]/resume-detail-page.tsx new file mode 100644 index 0000000..3ff1e32 --- /dev/null +++ b/frontend/src/app/(app)/resume/[id]/resume-detail-page.tsx @@ -0,0 +1,71 @@ +"use client"; + +import Link from "next/link"; +import { useParams } from "next/navigation"; +import { ArrowLeft, Download } from "lucide-react"; + +import { Badge } from "@/components/ui/badge"; +import { Button } from "@/components/ui/button"; +import { + Card, + CardContent, + CardHeader, + CardTitle, +} from "@/components/ui/card"; +import { Skeleton } from "@/components/ui/skeleton"; +import { useResume } from "@/lib/hooks/use-api"; + +export default function ResumeDetailPage() { + const params = useParams<{ id: string }>(); + const id = params?.id; + const { data: resume, isLoading } = useResume(id); + + if (isLoading) { + return ; + } + + if (!resume) { + return ( +
+

Resume not found.

+ +
+ ); + } + + return ( +
+ + + + +
+ {resume.title} +

+ Created {new Date(resume.createdAt).toLocaleDateString()} +

+
+
+ {resume.isBase ? Base : null} + +
+ + + 
+            {resume.content}
+
+ + +
+ ); +} diff --git a/frontend/src/app/(auth)/sign-in/[[...sign-in]]/page.tsx b/frontend/src/app/(auth)/sign-in/[[...sign-in]]/page.tsx index 2b163ed..58fff8e 100644 --- a/frontend/src/app/(auth)/sign-in/[[...sign-in]]/page.tsx +++ b/frontend/src/app/(auth)/sign-in/[[...sign-in]]/page.tsx @@ -1,21 +1,9 @@ -import { SignIn } from "@clerk/nextjs"; +import { SignInView } from "./sign-in-view"; + +export function generateStaticParams() { + return [{ "sign-in": [] as string[] }]; +} export default function SignInPage() { - return ( -
-
-

- Welcome back -

-

- Sign in to access your dashboard and tailor new applications. -

-
- -
- ); + return ; } diff --git a/frontend/src/app/(auth)/sign-in/[[...sign-in]]/sign-in-view.tsx b/frontend/src/app/(auth)/sign-in/[[...sign-in]]/sign-in-view.tsx new file mode 100644 index 0000000..04198d3 --- /dev/null +++ b/frontend/src/app/(auth)/sign-in/[[...sign-in]]/sign-in-view.tsx @@ -0,0 +1,44 @@ +"use client"; + +import { useEffect } from "react"; +import { useRouter } from "next/navigation"; +import { SignIn, useAuth } from "@clerk/react"; + +export function SignInView() { + const { isLoaded, isSignedIn } = useAuth(); + const router = useRouter(); + + useEffect(() => { + if (isLoaded && isSignedIn) { + router.replace("/dashboard"); + } + }, [isLoaded, isSignedIn, router]); + + if (!isLoaded) { + return ( +
Loading…
+ ); + } + if (isSignedIn) { + return null; + } + + return ( +
+
+

Welcome back

+

+ Sign in to access your dashboard and tailor new applications. +

+
+ +
+ ); +} diff --git a/frontend/src/app/(auth)/sign-up/[[...sign-up]]/page.tsx b/frontend/src/app/(auth)/sign-up/[[...sign-up]]/page.tsx index deec056..22c3c81 100644 --- a/frontend/src/app/(auth)/sign-up/[[...sign-up]]/page.tsx +++ b/frontend/src/app/(auth)/sign-up/[[...sign-up]]/page.tsx @@ -1,21 +1,9 @@ -import { SignUp } from "@clerk/nextjs"; +import { SignUpView } from "./sign-up-view"; + +export function generateStaticParams() { + return [{ "sign-up": [] as string[] }]; +} export default function SignUpPage() { - return ( -
-
-

- Create your account -

-

- Join TalentStreamAI to generate tailored resumes and cover letters in seconds. -

-
- -
- ); + return ; } diff --git a/frontend/src/app/(auth)/sign-up/[[...sign-up]]/sign-up-view.tsx b/frontend/src/app/(auth)/sign-up/[[...sign-up]]/sign-up-view.tsx new file mode 100644 index 0000000..c1d5eee --- /dev/null +++ b/frontend/src/app/(auth)/sign-up/[[...sign-up]]/sign-up-view.tsx @@ -0,0 +1,47 @@ +"use client"; + +import { useEffect } from "react"; +import { useRouter } from "next/navigation"; +import { SignUp, useAuth } from "@clerk/react"; + +export function SignUpView() { + const { isLoaded, isSignedIn } = useAuth(); + const router = useRouter(); + + useEffect(() => { + if (isLoaded && isSignedIn) { + router.replace("/dashboard"); + } + }, [isLoaded, isSignedIn, router]); + + if (!isLoaded) { + return ( +
Loading…
+ ); + } + if (isSignedIn) { + return null; + } + + return ( +
+
+

+ Create your account +

+

+ Join TalentStreamAI to generate tailored resumes and cover letters in + seconds. +

+
+ +
+ ); +} diff --git a/frontend/src/app/globals.css b/frontend/src/app/globals.css index 8cb5fe8..42f156a 100644 --- a/frontend/src/app/globals.css +++ b/frontend/src/app/globals.css @@ -4,57 +4,144 @@ @layer base { :root { - --background: 0 0% 100%; - --foreground: 240 10% 3.9%; + /* Brand (design spec — hex; same names are overridden below for shadcn where needed) */ + --primary: #002723; + --primary-light: #003d38; + --primary-muted: #004d45; + --secondary: #c9a84c; + --secondary-light: #e8c96a; + --secondary-muted: #f0dfa0; + --bg: #fafaf8; + --bg-card: #ffffff; + --text-primary: #0d0d0b; + --text-secondary: #4a4a45; + --text-muted: #8a8a84; + --border: rgba(0, 39, 35, 0.1); + --border-card: rgba(0, 39, 35, 0.08); + + /* shadcn / Tailwind — HSL space-separated (opacity modifiers, e.g. bg-primary/5) */ + --background: 50 20% 98%; + --foreground: 60 8% 4%; --card: 0 0% 100%; - --card-foreground: 240 10% 3.9%; + --card-foreground: 60 8% 4%; --popover: 0 0% 100%; - --popover-foreground: 240 10% 3.9%; - --primary: 238 84% 59%; - --primary-foreground: 0 0% 98%; - --secondary: 240 4.8% 95.9%; - --secondary-foreground: 240 5.9% 10%; - --muted: 240 4.8% 95.9%; - --muted-foreground: 240 3.8% 46.1%; - --accent: 240 4.8% 95.9%; - --accent-foreground: 240 5.9% 10%; - --destructive: 0 84.2% 60.2%; + --popover-foreground: 60 8% 4%; + --primary: 175 100% 7.6%; + --primary-foreground: 50 20% 98%; + --secondary: 50 25% 95%; + --secondary-foreground: 60 8% 10%; + --muted: 50 20% 96%; + --muted-foreground: 60 3% 30%; + --accent: 50 25% 95%; + --accent-foreground: 60 8% 10%; + --destructive: 0 84% 60%; --destructive-foreground: 0 0% 98%; - --border: 240 5.9% 90%; - --input: 240 5.9% 90%; - --ring: 238 84% 59%; + --border: 175 15% 90%; + --input: 175 15% 90%; + --ring: 175 100% 7.6%; --radius: 0.625rem; } .dark { - --background: 240 10% 3.9%; - --foreground: 0 0% 98%; - --card: 240 10% 3.9%; - --card-foreground: 0 0% 98%; - --popover: 240 10% 3.9%; - --popover-foreground: 0 0% 98%; - --primary: 238 84% 67%; - --primary-foreground: 240 5.9% 10%; - --secondary: 240 3.7% 15.9%; - --secondary-foreground: 0 0% 98%; - --muted: 240 3.7% 15.9%; - --muted-foreground: 240 5% 64.9%; - --accent: 240 3.7% 15.9%; - --accent-foreground: 0 0% 98%; - --destructive: 0 62.8% 30.6%; + --background: 175 18% 6%; + --foreground: 50 20% 98%; + --card: 175 16% 8%; + --card-foreground: 50 20% 98%; + --popover: 175 16% 8%; + --popover-foreground: 50 20% 98%; + --primary: 175 45% 42%; + --primary-foreground: 175 20% 8%; + --secondary: 175 12% 16%; + --secondary-foreground: 50 20% 98%; + --muted: 175 12% 16%; + --muted-foreground: 50 8% 65%; + --accent: 175 12% 16%; + --accent-foreground: 50 20% 98%; + --destructive: 0 62% 32%; --destructive-foreground: 0 0% 98%; - --border: 240 3.7% 15.9%; - --input: 240 3.7% 15.9%; - --ring: 238 84% 67%; + --border: 175 12% 18%; + --input: 175 12% 18%; + --ring: 175 45% 42%; } -} -@layer base { * { + box-sizing: border-box; + margin: 0; + padding: 0; @apply border-border; } + + html { + scroll-behavior: smooth; + } + body { @apply bg-background text-foreground; + -webkit-font-smoothing: antialiased; + -moz-osx-font-smoothing: grayscale; font-feature-settings: "rlig" 1, "calt" 1; } } + +@layer utilities { + .animate-fade-up { + animation: fadeUp 0.6s ease both; + } + + .animate-fade-up-1 { + animation: fadeUp 0.6s 0.1s ease both; + } + + .animate-fade-up-2 { + animation: fadeUp 0.6s 0.2s ease both; + } + + .animate-fade-up-3 { + animation: fadeUp 0.6s 0.3s ease both; + } + + .animate-fade-up-4 { + animation: fadeUp 0.6s 0.4s ease both; + } + + .animate-fade-up-5 { + animation: fadeUp 0.8s 0.5s ease both; + } + + @keyframes fadeUp { + from { + opacity: 0; + transform: translateY(24px); + } + to { + opacity: 1; + transform: translateY(0); + } + } + + @keyframes badgePulse { + 0%, + 100% { + opacity: 1; + transform: scale(1); + } + 50% { + opacity: 0.5; + transform: scale(0.85); + } + } + + .badge-pulse { + animation: badgePulse 2s infinite; + } + + @keyframes barFill { + from { + width: 0; + } + } + + .animate-bar-fill { + animation: barFill 1.2s 0.8s ease both; + } +} diff --git a/frontend/src/app/layout.tsx b/frontend/src/app/layout.tsx index f14aea2..a052859 100644 --- a/frontend/src/app/layout.tsx +++ b/frontend/src/app/layout.tsx @@ -1,40 +1,47 @@ import type { Metadata } from "next"; -import { Geist, Geist_Mono } from "next/font/google"; -import { ClerkProvider } from "@clerk/nextjs"; +import { Inter } from "next/font/google"; +import { ClerkProviderClient } from "@/components/clerk-provider"; import { Providers } from "@/components/providers"; import "./globals.css"; -const geistSans = Geist({ - variable: "--font-geist-sans", - subsets: ["latin"], -}); - -const geistMono = Geist_Mono({ - variable: "--font-geist-mono", - subsets: ["latin"], +const inter = Inter({ + subsets: ["latin"], + variable: "--font-inter", + display: "swap", }); export const metadata: Metadata = { - title: "TalentStreamAI", - description: - "AI-powered career co-pilot: tailored resumes, cover letters, and match scores in seconds.", + title: "TalentStreamAI — Land Interviews, Not Rejections", + description: + "AI-powered career co-pilot: tailored resumes, cover letters, and match scores in seconds.", + keywords: [ + "CV optimizer", + "ATS score", + "cover letter", + "job application", + "interview prep", + ], + openGraph: { + title: "TalentStreamAI — Land Interviews, Not Rejections", + description: + "AI-powered CV optimization that gets you interviews. Tailored CVs, cover letters, and interview prep in under 60 seconds.", + type: "website", + }, }; export default function RootLayout({ - children, + children, }: Readonly<{ - children: React.ReactNode; + children: React.ReactNode; }>) { - return ( - - - - {children} - - - - ); + return ( + + + + {children} + + + + ); } diff --git a/frontend/src/app/onboarding/page.tsx b/frontend/src/app/onboarding/page.tsx index 85788c2..890817a 100644 --- a/frontend/src/app/onboarding/page.tsx +++ b/frontend/src/app/onboarding/page.tsx @@ -2,7 +2,7 @@ import { useRouter } from "next/navigation"; import { useRef, useState } from "react"; -import { UserButton } from "@clerk/nextjs"; +import { UserButton } from "@clerk/react"; import { ArrowRight, Loader2, Upload } from "lucide-react"; import Link from "next/link"; @@ -40,7 +40,7 @@ export default function OnboardingPage() { TalentStreamAI - + @@ -51,7 +51,7 @@ export default function OnboardingPage() { Upload your base resume

- We'll use this as the foundation for every tailored application. + We'll use this as the foundation for every tailored application. You can always update it later.

diff --git a/frontend/src/app/page.tsx b/frontend/src/app/page.tsx index f97a656..981cd6a 100644 --- a/frontend/src/app/page.tsx +++ b/frontend/src/app/page.tsx @@ -1,45 +1,27 @@ -import Link from "next/link"; - -import LandingCta from "@/components/landing-cta"; -import LandingFeatures from "@/components/landing-features"; -import LandingFooter from "@/components/landing-footer"; -import LandingHero from "@/components/landing-hero"; -import LandingNavButtons from "@/components/landing-nav-buttons"; -import LandingProblemSolution from "@/components/landing-problem-solution"; -import LandingStats from "@/components/landing-stats"; -import LandingTestimonials from "@/components/landing-testimonials"; +import { CTA } from "@/components/landing/CTA"; +import { Features } from "@/components/landing/Features"; +import { Footer } from "@/components/landing/Footer"; +import { Hero } from "@/components/landing/Hero"; +import { HowItWorks } from "@/components/landing/HowItWorks"; +import { LogoBar } from "@/components/landing/LogoBar"; +import { Navbar } from "@/components/landing/Navbar"; +import { Outputs } from "@/components/landing/Outputs"; +import { Pricing } from "@/components/landing/Pricing"; +import { Stats } from "@/components/landing/Stats"; export default function LandingPage() { return ( -
- {/* Sticky header */} -
-
- - TalentStreamAI - - - -
-
- -
- - - - - - -
- - -
+
+ + + + + + + + + +
+
); } diff --git a/frontend/src/components/app-shell.tsx b/frontend/src/components/app-shell.tsx index 7460401..268a873 100644 --- a/frontend/src/components/app-shell.tsx +++ b/frontend/src/components/app-shell.tsx @@ -2,83 +2,87 @@ import Link from "next/link"; import { usePathname } from "next/navigation"; -import { UserButton } from "@clerk/nextjs"; +import { UserButton } from "@clerk/react"; import { FileText, LayoutDashboard, Sparkles, Send } from "lucide-react"; import { cn } from "@/lib/utils"; +import { LogoMark } from "./ui/logo-mark"; const NAV_ITEMS = [ - { href: "/dashboard", label: "Dashboard", icon: LayoutDashboard }, - { href: "/apply", label: "Apply", icon: Sparkles }, - { href: "/applications", label: "Applications", icon: Send }, - { href: "/resume", label: "Resumes", icon: FileText }, + { href: "/dashboard", label: "Dashboard", icon: LayoutDashboard }, + { href: "/apply", label: "Apply", icon: Sparkles }, + { href: "/applications", label: "Applications", icon: Send }, + { href: "/resume", label: "Resumes", icon: FileText }, ] as const; export function AppShell({ children }: { children: React.ReactNode }) { - const pathname = usePathname(); + const pathname = usePathname(); - return ( -
-
-
-
- - TalentStreamAI - - -
-
- -
+ return ( +
+
+
+
+ + + TalentStreamAI + + +
+
+ +
+
+ +
+
+ {children} +
- -
-
- {children} -
-
- ); + ); } diff --git a/frontend/src/components/clerk-provider.tsx b/frontend/src/components/clerk-provider.tsx new file mode 100644 index 0000000..485e79e --- /dev/null +++ b/frontend/src/components/clerk-provider.tsx @@ -0,0 +1,30 @@ +"use client"; + +import { ClerkProvider } from "@clerk/react"; + +const publishableKey = process.env.NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY; + +/** + * Client-only Clerk provider so `output: "export"` does not pull in App Router + * server actions from `@clerk/nextjs` (see Next.js static export limitations). + */ +export function ClerkProviderClient({ + children, +}: { + children: React.ReactNode; +}) { + if (!publishableKey) { + throw new Error("Missing NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY"); + } + + return ( + + {children} + + ); +} diff --git a/frontend/src/components/landing-cta.tsx b/frontend/src/components/landing-cta.tsx deleted file mode 100644 index 6b878c7..0000000 --- a/frontend/src/components/landing-cta.tsx +++ /dev/null @@ -1,44 +0,0 @@ -"use client"; - -import Link from "next/link"; -import { useAuth } from "@clerk/nextjs"; -import { ArrowRight } from "lucide-react"; - -import { Button } from "@/components/ui/button"; - -export default function LandingCta() { - const { isSignedIn } = useAuth(); - - return ( -
-
-

- Stop Sending Generic Applications -

-

- Start applying with resumes tailored to every job. -

-
- -
- {!isSignedIn && ( -

- No credit card required. -

- )} -
-
- ); -} diff --git a/frontend/src/components/landing-features.tsx b/frontend/src/components/landing-features.tsx deleted file mode 100644 index e22cbec..0000000 --- a/frontend/src/components/landing-features.tsx +++ /dev/null @@ -1,133 +0,0 @@ -import { ClipboardList, FileUp, Zap } from "lucide-react"; - -const STEPS = [ - { - step: "Step 1", - icon: ClipboardList, - title: "Paste Job Description", - body: "Copy the job posting and paste it in. We extract what matters — required skills, keywords, and role expectations.", - }, - { - step: "Step 2", - icon: FileUp, - title: "Upload Your Resume", - body: "Upload your existing resume in PDF, DOCX, or TXT. We use it as the foundation for everything we generate.", - }, - { - step: "Step 3", - icon: Zap, - title: "Get Your Optimized Application", - body: "Receive a tailored resume, cover letter, draft email, and a match score with gap analysis — instantly.", - }, -] as const; - -/* Inline app mockup — no screenshot needed */ -function AppMockup() { - return ( -
- {/* fake browser chrome */} -
- - - -
- talenstreamai.com/apply -
-
- -
- {/* Left pane — input */} -
-

Upload Resume

-
- -

Drag and drop your resume here

-
- Choose File -
-
-
-

Your Resumes

-
- # John Smith.docx - - Selected - -
-
-
- - {/* Right pane — output preview */} -
-

Job Match Analysis

-
-
-

Original

-

45%

-
-
-
-
-
-

Tailored

-

75%

-
-
-
-
-
-

Improvement

-

+30%

-

After one extra tailoring pass

-
-
-
-

What We Improved

- {[ - "Repositioned security architecture work higher in the resume.", - "Strengthened Azure & O365 remediation language.", - "Improved keyword coverage around vulnerability management.", - ].map((t) => ( -

- - {t} -

- ))} -
-
-
-
- ); -} - -export default function LandingFeatures() { - return ( -
-
-
-

How It Works

-

- Three steps. Under a minute. Better results on every application. -

-
- -
- {STEPS.map(({ step, icon: Icon, title, body }) => ( -
-
- -
-

- {step} -

-

{title}

-

{body}

-
- ))} -
- - -
-
- ); -} diff --git a/frontend/src/components/landing-footer.tsx b/frontend/src/components/landing-footer.tsx deleted file mode 100644 index e6cb893..0000000 --- a/frontend/src/components/landing-footer.tsx +++ /dev/null @@ -1,38 +0,0 @@ -import Link from "next/link"; - -const NAV = [ - { label: "How It Works", href: "#how-it-works" }, - { label: "Log In", href: "/sign-in" }, - { label: "Sign Up", href: "/sign-up" }, - { label: "Privacy Policy", href: "/privacy" }, - { label: "Terms of Service", href: "/terms" }, - { label: "Contact Us", href: "mailto:hello@talenstreamai.com" }, -] as const; - -export default function LandingFooter() { - return ( -
-
-
- - TalentStreamAI - - -
-

- © {new Date().getFullYear()} TalentStreamAI. All rights reserved. -

-
-
- ); -} diff --git a/frontend/src/components/landing-hero.tsx b/frontend/src/components/landing-hero.tsx deleted file mode 100644 index ee56221..0000000 --- a/frontend/src/components/landing-hero.tsx +++ /dev/null @@ -1,97 +0,0 @@ -"use client"; - -import Link from "next/link"; -import { useAuth } from "@clerk/nextjs"; -import { ArrowRight } from "lucide-react"; - -import { Button } from "@/components/ui/button"; - -function ScorePreview() { - return ( -
-

- Example optimization -

-
- {/* Before */} -
- 45% -
-
-
- Before -
- - {/* Arrow */} - - - {/* After */} -
- 78% -
-
-
- After -
-
-

- See exactly what's holding your resume back and fix it in seconds. -

-
- ); -} - -export default function LandingHero() { - const { isSignedIn } = useAuth(); - - return ( -
-
-

- Applying to jobs has never -
- been easier. -

-

- Paste a job description. Instantly generate a tailored resume, cover - letter, and match score — all in one place. -

- -
- {isSignedIn ? ( - <> - - - - ) : ( - <> - - - - )} -
- {!isSignedIn && ( -

- No credit card required. Free to get started. -

- )} - - -
-
- ); -} diff --git a/frontend/src/components/landing-nav-buttons.tsx b/frontend/src/components/landing-nav-buttons.tsx deleted file mode 100644 index 28ecd02..0000000 --- a/frontend/src/components/landing-nav-buttons.tsx +++ /dev/null @@ -1,32 +0,0 @@ -"use client"; - -import Link from "next/link"; -import { useAuth } from "@clerk/nextjs"; - -import { Button } from "@/components/ui/button"; - -export default function LandingNavButtons() { - const { isSignedIn } = useAuth(); - - if (isSignedIn) { - return ( - - ); - } - - return ( -
- - Log in - - -
- ); -} diff --git a/frontend/src/components/landing-problem-solution.tsx b/frontend/src/components/landing-problem-solution.tsx deleted file mode 100644 index fb5b4a1..0000000 --- a/frontend/src/components/landing-problem-solution.tsx +++ /dev/null @@ -1,60 +0,0 @@ -import { Check, X } from "lucide-react"; - -const PROBLEMS = [ - "Your resume isn't tailored to the job", - "Missing keywords filter you out before a human sees it", - "Formatting breaks when scanned by tracking systems", - "You're sending the same generic application every time", -] as const; - -const SOLUTIONS = [ - "Get your ATS match score instantly", - "See exactly which keywords you're missing", - "Generate a tailored resume for each job", - "Create a targeted cover letter automatically", - "Draft a personalised outreach email in one click", - "Track all your applications in one place", -] as const; - -export default function LandingProblemSolution() { - return ( -
-
-
- {/* Problem */} -
-

- Why You're Not Getting Interviews -

-
    - {PROBLEMS.map((p) => ( -
  • - - {p} -
    • - ))} -
-

- That's why you can apply to dozens of jobs and hear nothing back. -

-
- - {/* Solution */} -
-

- Fix That in Seconds -

-
    - {SOLUTIONS.map((s) => ( -
  • - - {s} -
    • - ))} -
-
-
-
-
- ); -} diff --git a/frontend/src/components/landing-stats.tsx b/frontend/src/components/landing-stats.tsx deleted file mode 100644 index 3849f26..0000000 --- a/frontend/src/components/landing-stats.tsx +++ /dev/null @@ -1,25 +0,0 @@ -const STATS = [ - { value: "2,400+", label: "Active users" }, - { value: "8,900+", label: "Tailored resumes" }, - { value: "11,200+", label: "Applications tracked" }, -] as const; - -export default function LandingStats() { - return ( -
-
-
- {STATS.map(({ value, label }) => ( -
-

{value}

-

{label}

-
- ))} -
-

- Based on self-reported application tracking and user activity stored in the TalentStreamAI database. -

-
-
- ); -} diff --git a/frontend/src/components/landing-testimonials.tsx b/frontend/src/components/landing-testimonials.tsx deleted file mode 100644 index bd896f1..0000000 --- a/frontend/src/components/landing-testimonials.tsx +++ /dev/null @@ -1,69 +0,0 @@ -const TESTIMONIALS = [ - { - quote: - "With every application I could have a tailored resume and cover letter. That's wild.", - author: "Chris M.", - }, - { - quote: - "Wow. I'm very impressed already! I just tailored my resume to an AI Support Engineer role.", - author: "Simon D.", - }, - { - quote: - "I've truly never seen anything else that will customise a resume and cover letter in one spot.", - author: "Adam K.", - }, -] as const; - -function QuoteIcon() { - return ( - - - - ); -} - -export default function LandingTestimonials() { - return ( -
-
-

- What Job Seekers Are Saying -

-

- Real feedback from people actively using TalentStreamAI in their job search. -

- -
- {TESTIMONIALS.map(({ quote, author }) => ( -
-
- -

- {quote} -

-
-

- — {author} -

-
- ))} -
-
-
- ); -} diff --git a/frontend/src/components/landing/CTA.tsx b/frontend/src/components/landing/CTA.tsx new file mode 100644 index 0000000..eb81cd0 --- /dev/null +++ b/frontend/src/components/landing/CTA.tsx @@ -0,0 +1,42 @@ +"use client"; + +import Link from "next/link"; +import { ArrowRight } from "lucide-react"; +import { Button } from "@/components/ui/button"; +import { LandingCtaButton } from "./LandingCtaButton"; + +export function CTA() { + return ( +
+
+ {/* Radial glow */} +
+ +

+ Your next interview +
+ is one upload away +

+

+ Join thousands who stopped getting rejected and started getting hired. +

+ +
+ + Optimize my CV now + + + +
+
+
+ ); +} diff --git a/frontend/src/components/landing/FeatureItem.tsx b/frontend/src/components/landing/FeatureItem.tsx new file mode 100644 index 0000000..0044f16 --- /dev/null +++ b/frontend/src/components/landing/FeatureItem.tsx @@ -0,0 +1,21 @@ +interface FeatureItemProps { + icon: string; + title: string; + description: string; +} + +export function FeatureItem({ icon, title, description }: FeatureItemProps) { + return ( +
+
+ {icon} +
+

+ {title} +

+

+ {description} +

+
+ ); +} diff --git a/frontend/src/components/landing/Features.tsx b/frontend/src/components/landing/Features.tsx new file mode 100644 index 0000000..78ec78e --- /dev/null +++ b/frontend/src/components/landing/Features.tsx @@ -0,0 +1,72 @@ +import { SectionHeader } from "../ui/section-header"; +import { FeatureItem } from "./FeatureItem"; + +const features = [ + { + icon: "🤖", + title: "ATS Optimization", + description: + "We reverse-engineer what each company's ATS is looking for and rewrite your CV to score above 90 — consistently.", + }, + { + icon: "✍️", + title: "Cover Letter Generator", + description: + "Compelling, personalized cover letters that match your voice and the company's tone. Never generic, never a template.", + }, + { + icon: "🔍", + title: "Keyword Analysis", + description: + "See exactly which keywords the job requires, which ones you're missing, and why each one matters.", + }, + { + icon: "💼", + title: "LinkedIn Headline", + description: + "Your LinkedIn profile rewritten to attract recruiters searching for this exact role — optimized for search rankings.", + }, + { + icon: "🎤", + title: "Interview Prep", + description: + "Role-specific questions, STAR-format answer frameworks, and the top 10 questions this company historically asks.", + }, + { + icon: "📊", + title: "Gap Analysis", + description: + "Understand what skills or experience are missing and get actionable suggestions to close the gap before applying.", + }, +]; + +export function Features() { + return ( +
+
+ + Everything you need +
+ to get the offer + + } + description="One upload. A complete application package built specifically for each role." + dark + /> + + {/* Grid with 1px gap separator effect */} +
+ {features.map((feature) => ( + + ))} +
+
+
+ ); +} diff --git a/frontend/src/components/landing/Footer.tsx b/frontend/src/components/landing/Footer.tsx new file mode 100644 index 0000000..d88d780 --- /dev/null +++ b/frontend/src/components/landing/Footer.tsx @@ -0,0 +1,43 @@ +import Link from "next/link"; +import { LogoMark } from "@/components/ui/logo-mark"; + +const footerLinks = [ + { href: "/privacy", label: "Privacy" }, + { href: "/terms", label: "Terms" }, + { href: "/blog", label: "Blog" }, + { href: "/support", label: "Support" }, +]; + +export function Footer() { + return ( +
+ + + + TalentStreamAI + + + +
    + {footerLinks.map((link) => ( +
  • + + {link.label} + +
    • + ))} +
+ +

+ © {new Date().getFullYear()} TalentStreamAI. All rights + reserved. +

+
+ ); +} diff --git a/frontend/src/components/landing/Hero.tsx b/frontend/src/components/landing/Hero.tsx new file mode 100644 index 0000000..5abee98 --- /dev/null +++ b/frontend/src/components/landing/Hero.tsx @@ -0,0 +1,106 @@ +"use client"; + +import Link from "next/link"; +import { ArrowRight, HelpCircle } from "lucide-react"; +import { Button } from "@/components/ui/button"; +import { Badge } from "@/components/ui/badge"; +import { LandingCtaButton } from "./LandingCtaButton"; +import { HeroMockup } from "./HeroMockup"; + +const avatars = [ + { initials: "AK", bg: "#1B4D3E" }, + { initials: "LM", bg: "#C9A84C" }, + { initials: "BO", bg: "#3D6B5E" }, + { initials: "FN", bg: "#8B6B1A" }, +]; + +export function Hero() { + return ( +
+ {/* Background radial glows */} +
+
+
+
+ + {/* Hero badge */} +
+ + + AI-powered job application suite + +
+ + {/* Headline */} +

+ Stop getting ignored.{" "} + + Start getting interviews. + +

+ + {/* Subheadline */} +

+ Upload your CV, paste any job link — we rewrite your application to beat + ATS filters and land in front of the hiring manager. +

+ + {/* CTA buttons */} +
+ + Optimize my CV — it's free + + + +
+ + {/* Social proof */} +
+
+ {avatars.map((av, i) => ( +
+ {av.initials} +
+ ))} +
+

+ 4,200+ job seekers got + interviews this month +

+
+ + {/* Mockup visual */} + +
+ ); +} diff --git a/frontend/src/components/landing/HeroMockup.tsx b/frontend/src/components/landing/HeroMockup.tsx new file mode 100644 index 0000000..68804c7 --- /dev/null +++ b/frontend/src/components/landing/HeroMockup.tsx @@ -0,0 +1,120 @@ +export function HeroMockup() { + const bars = [ + { label: "Keywords matched", value: 96 }, + { label: "Format score", value: 92 }, + { label: "Relevance", value: 90 }, + ]; + + const tags = ["Python", "React", "CI/CD", "Agile"]; + + return ( +
+ {/* Window chrome */} +
+
+ {/* Title bar */} +
+ + + +
+ app.talentstreamai.ai/optimize +
+
+ + {/* Body — two panels */} +
+ {/* ATS Score Panel */} +
+

+ ATS Score +

+
+ + 94 + + + / 100 + +
+ + {bars.map((bar) => ( +
+
+ {bar.label} + {bar.value}% +
+
+
+
+
+ ))} + +
+ {tags.map((tag) => ( + + + ✓ + + {tag} + + ))} +
+
+ + {/* CV Preview Panel */} +
+

+ Optimized CV +

+ {[ + 100, + 65, + null, + 100, + 100, + 45, + null, + 100, + 65, + 100, + ].map((w, i) => + w === null ? ( +
+ ) : ( +
+ ), + )} +
+
+ + Ready to download +
+
+
+
+
+
+
+ ); +} diff --git a/frontend/src/components/landing/HowItWorks.tsx b/frontend/src/components/landing/HowItWorks.tsx new file mode 100644 index 0000000..4aa1da0 --- /dev/null +++ b/frontend/src/components/landing/HowItWorks.tsx @@ -0,0 +1,57 @@ +import { SectionHeader } from "@/components/ui/section-header"; +import { StepCard } from "./StepCard"; + +const steps = [ + { + step: 1, + label: "Upload", + icon: "📄", + title: "Drop your CV", + description: + "Upload your existing CV in any format — PDF, DOCX, or paste the text. We handle the rest.", + }, + { + step: 2, + label: "Target", + icon: "🎯", + title: "Paste the job link", + description: + "Add the URL or description of the role you want. Our AI reads the job post and extracts every requirement.", + }, + { + step: 3, + label: "Download", + icon: "✨", + title: "Get your full kit", + description: + "Receive an ATS-optimized CV, tailored cover letter, LinkedIn summary, and interview prep — all in under 60 seconds.", + }, +]; + +export function HowItWorks() { + return ( +
+ + Three steps to your +
+ next interview + + } + description="No more guessing if your CV is good enough. We guarantee it is." + /> + +
+ {steps.map((step, i) => ( + + ))} +
+
+ ); +} diff --git a/frontend/src/components/landing/LandingCtaButton.tsx b/frontend/src/components/landing/LandingCtaButton.tsx new file mode 100644 index 0000000..9d54844 --- /dev/null +++ b/frontend/src/components/landing/LandingCtaButton.tsx @@ -0,0 +1,42 @@ +"use client"; + +import type { ReactNode } from "react"; +import Link from "next/link"; +import { useAuth } from "@clerk/react"; + +import { Button, type ButtonProps } from "@/components/ui/button"; + +type LandingCtaButtonProps = Omit & { + children: ReactNode; +}; + +/** + * Primary landing CTAs: /dashboard for signed-in users, /sign-up for guests + * (matches middleware redirect for authenticated visits to /sign-in and /sign-up). + */ +export function LandingCtaButton({ children, disabled, ...buttonProps }: LandingCtaButtonProps) { + const { isSignedIn, isLoaded } = useAuth(); + const href = isSignedIn ? "/dashboard" : "/sign-up"; + + if (!isLoaded) { + return ( + + ); + } + + if (disabled) { + return ( + + ); + } + + return ( + + ); +} diff --git a/frontend/src/components/landing/LogoBar.tsx b/frontend/src/components/landing/LogoBar.tsx new file mode 100644 index 0000000..cd124cc --- /dev/null +++ b/frontend/src/components/landing/LogoBar.tsx @@ -0,0 +1,21 @@ +const companies = ["Google", "Stripe", "McKinsey", "Shopify", "Notion", "Airbnb"]; + +export function LogoBar() { + return ( +
+

+ Used by candidates targeting +

+
+ {companies.map((name) => ( + + {name} + + ))} +
+
+ ); +} diff --git a/frontend/src/components/landing/Navbar.tsx b/frontend/src/components/landing/Navbar.tsx new file mode 100644 index 0000000..51cc034 --- /dev/null +++ b/frontend/src/components/landing/Navbar.tsx @@ -0,0 +1,70 @@ +"use client"; + +import Link from "next/link"; +import { SignInButton, UserButton, useAuth } from "@clerk/react"; +import { ArrowRight } from "lucide-react"; +import { LogoMark } from "@/components/ui/logo-mark"; +import { Button } from "@/components/ui/button"; +import { LandingCtaButton } from "./LandingCtaButton"; + +const navLinks = [ + { href: "#how-it-works", label: "How it works" }, + { href: "#features", label: "Features" }, + { href: "#pricing", label: "Pricing" }, +]; + +export function Navbar() { + const { isSignedIn, isLoaded } = useAuth(); + + return ( + + ); +} diff --git a/frontend/src/components/landing/OutputPreview.tsx b/frontend/src/components/landing/OutputPreview.tsx new file mode 100644 index 0000000..61ad48b --- /dev/null +++ b/frontend/src/components/landing/OutputPreview.tsx @@ -0,0 +1,74 @@ +import { Badge } from "@/components/ui/badge"; + +const keywords = [ + { text: "Product Management", highlight: true }, + { text: "Roadmapping", highlight: true }, + { text: "Agile", highlight: true }, + { text: "Stakeholder mgmt", highlight: false }, + { text: "Data-driven", highlight: true }, + { text: "B2B SaaS", highlight: false }, + { text: "OKRs", highlight: true }, + { text: "GTM strategy", highlight: false }, +]; + +export function OutputPreview() { + return ( +
+ {/* Header */} +
+ + CV Score Report + + + 94 / 100 + +
+ + {/* Body */} +
+ {/* Score row */} +
+
+

+ ATS Score +

+

+ 94 + + /100 + +

+
+ ✓ Interview-ready +
+ + {/* Keywords */} +

+ Matched keywords +

+
+ {keywords.map((kw) => ( + + {kw.text} + + ))} +
+ + {/* Experience lines */} +

+ Experience summary +

+ {[100, 75, 100, 50].map((w, i) => ( +
+ ))} +
+
+ ); +} diff --git a/frontend/src/components/landing/Outputs.tsx b/frontend/src/components/landing/Outputs.tsx new file mode 100644 index 0000000..fc23068 --- /dev/null +++ b/frontend/src/components/landing/Outputs.tsx @@ -0,0 +1,85 @@ +"use client"; + +import { useState } from "react"; +import { SectionHeader } from "@/components/ui/section-header"; +import { OutputPreview } from "./OutputPreview"; +import { cn } from "@/lib/utils"; + +const outputs = [ + { + icon: "📄", + title: "ATS-Optimized CV", + description: "Tailored to the job description. Scores above 90 on every major ATS.", + }, + { + icon: "✉️", + title: "Cover Letter", + description: "Personalized, compelling, and formatted for the role and company.", + }, + { + icon: "🔗", + title: "LinkedIn Summary", + description: "Rewritten about section optimized for recruiter searches.", + }, + { + icon: "❓", + title: "Interview Question Bank", + description: "10 role-specific questions with suggested STAR-format answers.", + }, +]; + +export function Outputs() { + const [activeIndex, setActiveIndex] = useState(0); + + return ( +
+ + Your complete +
+ application kit + + } + description="Every document you need to apply with confidence, all generated in one go." + /> + +
+ {/* Output list */} +
+ {outputs.map((item, i) => ( + + ))} +
+ + {/* Preview panel */} + +
+
+ ); +} diff --git a/frontend/src/components/landing/Pricing.tsx b/frontend/src/components/landing/Pricing.tsx new file mode 100644 index 0000000..a516daf --- /dev/null +++ b/frontend/src/components/landing/Pricing.tsx @@ -0,0 +1,68 @@ +import { SectionHeader } from "@/components/ui/section-header"; +import { PricingCard } from "./PricingCard"; + +const plans = [ + { + plan: "Starter", + price: "Free", + period: "3 optimizations / month", + features: [ + "ATS-optimized CV", + "Keyword analysis", + "Basic cover letter", + "PDF download", + ], + ctaLabel: "Get started free", + featured: false, + }, + { + plan: "Pro", + price: "$19", + period: "per month, billed monthly", + features: [ + "Unlimited optimizations", + "Full cover letter suite", + "LinkedIn rewrite", + "Interview question bank", + "Gap analysis", + "Priority processing", + ], + ctaLabel: "Start with Pro", + featured: true, + badge: "Most popular", + }, + { + plan: "Teams", + price: "$49", + period: "per month, up to 5 members", + features: [ + "Everything in Pro", + "Team dashboard", + "Recruiter collaboration", + "Bulk CV processing", + "Analytics & reporting", + "Dedicated support", + ], + ctaLabel: "Contact sales", + featured: false, + }, +]; + +export function Pricing() { + return ( +
+ + +
+ {plans.map((plan) => ( + + ))} +
+
+ ); +} diff --git a/frontend/src/components/landing/PricingCard.tsx b/frontend/src/components/landing/PricingCard.tsx new file mode 100644 index 0000000..9c002cd --- /dev/null +++ b/frontend/src/components/landing/PricingCard.tsx @@ -0,0 +1,107 @@ +"use client"; + +import { cn } from "@/lib/utils"; +import { LandingCtaButton } from "./LandingCtaButton"; + +interface PricingCardProps { + plan: string; + price: string; + period: string; + features: string[]; + ctaLabel: string; + featured?: boolean; + badge?: string; +} + +export function PricingCard({ + plan, + price, + period, + features, + ctaLabel, + featured = false, + badge, +}: PricingCardProps) { + return ( +
+ {badge && ( + + {badge} + + )} + +

+ {plan} +

+ +

+ {price} +

+

+ {period} +

+ +
+ +
    + {features.map((feature) => ( +
  • + + ✓ + + + {feature} + +
    • + ))} +
+ + + {ctaLabel} + +
+ ); +} diff --git a/frontend/src/components/landing/Stats.tsx b/frontend/src/components/landing/Stats.tsx new file mode 100644 index 0000000..4180c7b --- /dev/null +++ b/frontend/src/components/landing/Stats.tsx @@ -0,0 +1,30 @@ +const stats = [ + { number: "94", suffix: "%", label: "Average ATS score" }, + { number: "3", suffix: "×", label: "More interview callbacks" }, + { number: "60", suffix: "s", label: "To full application kit" }, + { number: "4.2", suffix: "k", label: "Interviews landed this month" }, +]; + +export function Stats() { + return ( +
+
+ {stats.map((stat) => ( +
+

+ {stat.number} + {stat.suffix} +

+

{stat.label}

+
+ ))} +
+
+ ); +} diff --git a/frontend/src/components/landing/StepCard.tsx b/frontend/src/components/landing/StepCard.tsx new file mode 100644 index 0000000..6bb8d26 --- /dev/null +++ b/frontend/src/components/landing/StepCard.tsx @@ -0,0 +1,46 @@ +interface StepCardProps { + step: number; + label: string; + icon: string; + title: string; + description: string; + showConnector?: boolean; +} + +export function StepCard({ + step, + label, + icon, + title, + description, + showConnector = false, +}: StepCardProps) { + return ( +
+ {/* Step number */} +
+
+ {step} +
+ {label} +
+ + {/* Icon */} +
+ {icon} +
+ +

+ {title} +

+

{description}

+ + {/* Connector arrow */} + {showConnector && ( +
+ → +
+ )} +
+ ); +} diff --git a/frontend/src/components/match-badge.tsx b/frontend/src/components/match-badge.tsx index 3944f3a..8b5a8f9 100644 --- a/frontend/src/components/match-badge.tsx +++ b/frontend/src/components/match-badge.tsx @@ -6,8 +6,8 @@ type MatchBadgeProps = { }; export function MatchBadge({ score, className }: MatchBadgeProps) { - const variant: "default" | "warning" | "destructive" = - score >= 85 ? "default" : score >= 70 ? "warning" : "destructive"; + const variant: "score" | "warning" | "destructive" = + score >= 85 ? "score" : score >= 70 ? "warning" : "destructive"; return ( diff --git a/frontend/src/components/status-badge.tsx b/frontend/src/components/status-badge.tsx index 40d3478..0a155d8 100644 --- a/frontend/src/components/status-badge.tsx +++ b/frontend/src/components/status-badge.tsx @@ -11,12 +11,12 @@ const LABELS: Record = { const VARIANTS: Record< ApplicationStatus, - "secondary" | "info" | "default" | "success" | "destructive" + "secondary" | "keyword" | "section" | "score" | "destructive" > = { draft: "secondary", - applied: "info", - interview: "default", - offer: "success", + applied: "keyword", + interview: "section", + offer: "score", rejected: "destructive", }; diff --git a/frontend/src/components/ui/badge.tsx b/frontend/src/components/ui/badge.tsx index 318060d..b9e85f8 100644 --- a/frontend/src/components/ui/badge.tsx +++ b/frontend/src/components/ui/badge.tsx @@ -1,39 +1,49 @@ import * as React from "react"; import { cva, type VariantProps } from "class-variance-authority"; - import { cn } from "@/lib/utils"; const badgeVariants = cva( - "inline-flex items-center rounded-full border px-2.5 py-0.5 text-xs font-semibold transition-colors focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2", - { - variants: { - variant: { - default: - "border-transparent bg-primary text-primary-foreground hover:bg-primary/80", - secondary: - "border-transparent bg-secondary text-secondary-foreground hover:bg-secondary/80", - destructive: - "border-transparent bg-destructive text-destructive-foreground hover:bg-destructive/80", - outline: "text-foreground", - success: "border-transparent bg-emerald-100 text-emerald-800", - warning: "border-transparent bg-amber-100 text-amber-800", - info: "border-transparent bg-blue-100 text-blue-800", - }, - }, - defaultVariants: { - variant: "default", + "inline-flex items-center gap-2 font-semibold transition-colors", + { + variants: { + variant: { + /** Neutral / muted; common shadcn name for app UI like “Base” labels */ + secondary: + "bg-[rgba(0,39,35,0.08)] text-[#002723] text-[12px] px-[10px] py-1 rounded-full font-medium border border-[rgba(0,39,35,0.12)]", + hero: "bg-[rgba(201,168,76,0.12)] border border-[rgba(201,168,76,0.3)] text-[#8B6B1A] text-[12.5px] px-[14px] py-[5px] rounded-full tracking-[0.3px]", + section: + "bg-[rgba(0,39,35,0.06)] text-[#002723] text-[12px] px-[14px] py-[5px] rounded-full uppercase tracking-[0.5px]", + "section-dark": + "bg-[rgba(201,168,76,0.12)] border border-[rgba(201,168,76,0.2)] text-[#E8C96A] text-[12px] px-[14px] py-[5px] rounded-full uppercase tracking-[0.5px]", + featured: + "bg-[rgba(201,168,76,0.12)] border border-[rgba(201,168,76,0.25)] text-[#E8C96A] text-[11px] px-[10px] py-[3px] rounded-full tracking-[0.5px]", + score: "bg-[rgba(74,222,128,0.1)] border border-[rgba(74,222,128,0.3)] text-[#166534] text-[12px] px-[12px] py-[5px] rounded-full", + warning: + "bg-[rgba(234,179,8,0.12)] border border-[rgba(202,138,4,0.35)] text-[#a16207] text-[12px] px-[12px] py-[5px] rounded-full", + destructive: + "bg-[rgba(248,113,113,0.12)] border border-[rgba(220,38,38,0.35)] text-[#b91c1c] text-[12px] px-[12px] py-[5px] rounded-full", + keyword: + "bg-[rgba(0,39,35,0.06)] text-[#002723] text-[11px] px-[10px] py-1 rounded-full font-medium", + "keyword-highlight": + "bg-[rgba(201,168,76,0.1)] border border-[rgba(201,168,76,0.25)] text-[#8B6B1A] text-[11px] px-[10px] py-1 rounded-full font-medium", + ats: "bg-[rgba(201,168,76,0.12)] border border-[rgba(201,168,76,0.22)] text-[#f0dfa0] text-[11px] px-[10px] py-1 rounded-full font-medium", + }, + }, + defaultVariants: { + variant: "section", + }, }, - }, ); export interface BadgeProps - extends React.HTMLAttributes, - VariantProps {} + extends + React.HTMLAttributes, + VariantProps {} function Badge({ className, variant, ...props }: BadgeProps) { - return ( -
- ); + return ( +
+ ); } export { Badge, badgeVariants }; diff --git a/frontend/src/components/ui/button.tsx b/frontend/src/components/ui/button.tsx index 231ff3c..923ff27 100644 --- a/frontend/src/components/ui/button.tsx +++ b/frontend/src/components/ui/button.tsx @@ -1,56 +1,64 @@ import * as React from "react"; import { Slot } from "@radix-ui/react-slot"; import { cva, type VariantProps } from "class-variance-authority"; - import { cn } from "@/lib/utils"; const buttonVariants = cva( - "inline-flex items-center justify-center whitespace-nowrap rounded-md text-sm font-medium transition-colors focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 disabled:pointer-events-none disabled:opacity-50", - { - variants: { - variant: { - default: "bg-primary text-primary-foreground hover:bg-primary/90", - destructive: - "bg-destructive text-destructive-foreground hover:bg-destructive/90", - outline: - "border border-input bg-background hover:bg-accent hover:text-accent-foreground", - secondary: - "bg-secondary text-secondary-foreground hover:bg-secondary/80", - ghost: "hover:bg-accent hover:text-accent-foreground", - link: "text-primary underline-offset-4 hover:underline", - }, - size: { - default: "h-10 px-4 py-2", - sm: "h-9 rounded-md px-3", - lg: "h-11 rounded-md px-8", - icon: "h-10 w-10", - }, - }, - defaultVariants: { - variant: "default", - size: "default", + "inline-flex items-center justify-center gap-2 whitespace-nowrap font-semibold transition-all duration-200 cursor-pointer select-none focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-[#002723] focus-visible:ring-offset-2 disabled:pointer-events-none disabled:opacity-50", + { + variants: { + variant: { + primary: + "bg-[#002723] text-[#FAFAF8] rounded-[6px] shadow-[0_4px_24px_rgba(0,39,35,0.2)] hover:bg-[#003d38] hover:-translate-y-[1px] hover:shadow-[0_8px_32px_rgba(0,39,35,0.28)] active:translate-y-0", + /** Secondary action; same visual as ghost, named for shadcn / common API compatibility */ + outline: + "bg-transparent text-[#002723] border border-[rgba(0,39,35,0.1)] rounded-[6px] hover:bg-[rgba(0,39,35,0.05)] hover:border-[rgba(0,39,35,0.25)]", + ghost: "bg-transparent text-[#002723] border border-[rgba(0,39,35,0.1)] rounded-[6px] hover:bg-[rgba(0,39,35,0.05)] hover:border-[rgba(0,39,35,0.25)]", + hero: "bg-[#002723] text-[#FAFAF8] rounded-[12px] shadow-[0_4px_24px_rgba(0,39,35,0.2)] hover:bg-[#004d45] hover:-translate-y-[2px] hover:shadow-[0_8px_32px_rgba(0,39,35,0.28)] active:translate-y-0", + "hero-secondary": + "bg-transparent text-[#002723] border border-[rgba(0,39,35,0.1)] rounded-[12px] hover:bg-[rgba(0,39,35,0.04)]", + gold: "bg-[#C9A84C] text-[#002723] rounded-[12px] shadow-[0_4px_20px_rgba(201,168,76,0.3)] hover:bg-[#E8C96A] hover:-translate-y-[2px] hover:shadow-[0_8px_28px_rgba(201,168,76,0.4)] active:translate-y-0", + "ghost-dark": + "bg-[rgba(255,255,255,0.06)] text-[rgba(245,245,240,0.8)] border border-[rgba(255,255,255,0.12)] rounded-[12px] hover:bg-[rgba(255,255,255,0.1)]", + "pricing-ghost": + "bg-transparent text-[#002723] border border-[rgba(0,39,35,0.1)] rounded-[6px] hover:bg-[rgba(0,39,35,0.05)] w-full", + "pricing-primary": + "bg-[#C9A84C] text-[#002723] rounded-[6px] hover:bg-[#E8C96A] hover:-translate-y-[1px] w-full", + }, + size: { + sm: "h-8 px-4 text-[13px]", + md: "h-9 px-[18px] text-[14px]", + lg: "h-[46px] px-7 text-[15px]", + xl: "h-[50px] px-8 text-[15px]", + }, + }, + defaultVariants: { + variant: "primary", + size: "md", + }, }, - }, ); export interface ButtonProps - extends React.ButtonHTMLAttributes, - VariantProps { - asChild?: boolean; + extends + React.ButtonHTMLAttributes, + VariantProps { + asChild?: boolean; } const Button = React.forwardRef( - ({ className, variant, size, asChild = false, ...props }, ref) => { - const Comp = asChild ? Slot : "button"; - return ( - - ); - }, + ({ className, variant, size, asChild = false, ...props }, ref) => { + const Comp = asChild ? Slot : "button"; + return ( + + ); + }, ); + Button.displayName = "Button"; export { Button, buttonVariants }; diff --git a/frontend/src/components/ui/card.tsx b/frontend/src/components/ui/card.tsx index 9bd88de..dd4fea3 100644 --- a/frontend/src/components/ui/card.tsx +++ b/frontend/src/components/ui/card.tsx @@ -1,86 +1,77 @@ import * as React from "react"; - import { cn } from "@/lib/utils"; const Card = React.forwardRef< - HTMLDivElement, - React.HTMLAttributes + HTMLDivElement, + React.HTMLAttributes >(({ className, ...props }, ref) => ( -
+
)); Card.displayName = "Card"; const CardHeader = React.forwardRef< - HTMLDivElement, - React.HTMLAttributes + HTMLDivElement, + React.HTMLAttributes >(({ className, ...props }, ref) => ( -
+
)); CardHeader.displayName = "CardHeader"; const CardTitle = React.forwardRef< - HTMLDivElement, - React.HTMLAttributes + HTMLHeadingElement, + React.HTMLAttributes >(({ className, ...props }, ref) => ( -

+

)); CardTitle.displayName = "CardTitle"; const CardDescription = React.forwardRef< - HTMLDivElement, - React.HTMLAttributes + HTMLParagraphElement, + React.HTMLAttributes >(({ className, ...props }, ref) => ( -

+

)); CardDescription.displayName = "CardDescription"; const CardContent = React.forwardRef< - HTMLDivElement, - React.HTMLAttributes + HTMLDivElement, + React.HTMLAttributes >(({ className, ...props }, ref) => ( -

+
)); CardContent.displayName = "CardContent"; const CardFooter = React.forwardRef< - HTMLDivElement, - React.HTMLAttributes + HTMLDivElement, + React.HTMLAttributes >(({ className, ...props }, ref) => ( -
+
)); CardFooter.displayName = "CardFooter"; export { - Card, - CardHeader, - CardFooter, - CardTitle, - CardDescription, - CardContent, + Card, + CardHeader, + CardTitle, + CardDescription, + CardContent, + CardFooter, }; diff --git a/frontend/src/components/ui/logo-mark.tsx b/frontend/src/components/ui/logo-mark.tsx new file mode 100644 index 0000000..68a7f01 --- /dev/null +++ b/frontend/src/components/ui/logo-mark.tsx @@ -0,0 +1,39 @@ +import { cn } from "@/lib/utils"; + +interface LogoMarkProps { + size?: number; + className?: string; +} + +export function LogoMark({ size = 32, className }: LogoMarkProps) { + const iconSize = Math.round(size * 0.5); + return ( +
+ +
+ ); +} diff --git a/frontend/src/components/ui/section-header.tsx b/frontend/src/components/ui/section-header.tsx new file mode 100644 index 0000000..5726aea --- /dev/null +++ b/frontend/src/components/ui/section-header.tsx @@ -0,0 +1,61 @@ +import { cn } from "@/lib/utils"; +import { Badge } from "@/components/ui/badge"; +import type { BadgeProps } from "@/components/ui/badge"; + +interface SectionHeaderProps { + tag: string; + title: React.ReactNode; + description?: string; + align?: "left" | "center"; + dark?: boolean; + className?: string; + descriptionClassName?: string; +} + +export function SectionHeader({ + tag, + title, + description, + align = "left", + dark = false, + className, + descriptionClassName, +}: SectionHeaderProps) { + const badgeVariant: BadgeProps["variant"] = dark + ? "section-dark" + : "section"; + + return ( +
+ + {tag} + +

+ {title} +

+ {description && ( +

+ {description} +

+ )} +
+ ); +} diff --git a/frontend/src/lib/api.ts b/frontend/src/lib/api.ts index 500e6f6..0fcf03d 100644 --- a/frontend/src/lib/api.ts +++ b/frontend/src/lib/api.ts @@ -63,15 +63,16 @@ export async function apiFetch( const parsed = text ? safeJsonParse(text) : undefined; if (!response.ok) { - const message = - (parsed && - typeof parsed === "object" && - parsed !== null && - "detail" in parsed && - typeof (parsed as { detail: unknown }).detail === "string" && - (parsed as { detail: string }).detail) || - response.statusText || - "Request failed"; + let message: string = response.statusText || "Request failed"; + if ( + parsed && + typeof parsed === "object" && + parsed !== null && + "detail" in parsed && + typeof (parsed as { detail: unknown }).detail === "string" + ) { + message = (parsed as { detail: string }).detail; + } throw new ApiError(message, response.status, parsed); } diff --git a/frontend/src/lib/hooks/use-api.ts b/frontend/src/lib/hooks/use-api.ts index aead8de..97506bf 100644 --- a/frontend/src/lib/hooks/use-api.ts +++ b/frontend/src/lib/hooks/use-api.ts @@ -1,6 +1,6 @@ "use client"; -import { useAuth } from "@clerk/nextjs"; +import { useAuth } from "@clerk/react"; import { useMutation, useQuery, diff --git a/frontend/src/lib/mock-data.ts b/frontend/src/lib/mock-data.ts index 0a9ac58..c44c1ec 100644 --- a/frontend/src/lib/mock-data.ts +++ b/frontend/src/lib/mock-data.ts @@ -141,6 +141,7 @@ export const mockApi = { return delay(resumes.find((r) => r.id === id)); }, async tailor(req: TailorRequest): Promise { + void req; const id = `a-${Date.now()}`; const resumeId = `r-${Date.now()}`; diff --git a/frontend/tsconfig.json b/frontend/tsconfig.json index c133409..d9aa91a 100644 --- a/frontend/tsconfig.json +++ b/frontend/tsconfig.json @@ -1,5 +1,6 @@ { "compilerOptions": { + "baseUrl": ".", "target": "ES2017", "lib": ["dom", "dom.iterable", "esnext"], "allowJs": true, From 967b5edf8d598a34c9ee745abffcc5c4ffef7b89 Mon Sep 17 00:00:00 2001 From: iamwales Date: Fri, 24 Apr 2026 07:11:52 +0100 Subject: [PATCH 2/6] feat: implemented all neccessary apis needed for the frontend and observability with error handling --- .env.example | 13 +- backend/app/api/router.py | 16 +- backend/app/api/schemas/frontend.py | 207 +++++++++++ backend/app/api/v1/applications.py | 88 +++++ backend/app/api/v1/dashboard.py | 22 ++ backend/app/api/v1/observability.py | 36 ++ backend/app/api/v1/profile.py | 39 ++ backend/app/api/v1/resumes.py | 121 +++---- backend/app/core/auth.py | 9 +- backend/app/core/config.py | 9 + backend/app/core/db.py | 335 ++++++++++++++++++ backend/app/core/exception_handlers.py | 35 ++ backend/app/core/logging_config.py | 43 +++ backend/app/core/metrics.py | 43 +++ backend/app/core/request_context.py | 47 +++ backend/app/main.py | 16 +- backend/app/middleware/request_context.py | 59 +++ backend/app/services/draft_email.py | 43 +++ backend/app/services/ingest_resume.py | 106 ++++++ backend/app/services/job_text.py | 34 ++ .../app/services/langgraph/streaming_agent.py | 32 +- backend/app/services/langgraph/workflow.py | 48 ++- backend/app/services/llm/client.py | 44 ++- backend/app/services/llm/safety.py | 23 ++ backend/app/services/tailor_orchestrator.py | 184 ++++++++++ backend/docs/ARCHITECTURE.md | 43 +++ backend/pyproject.toml | 4 + backend/uv.lock | 317 +++++++++++++++++ 28 files changed, 1925 insertions(+), 91 deletions(-) create mode 100644 backend/app/api/schemas/frontend.py create mode 100644 backend/app/api/v1/applications.py create mode 100644 backend/app/api/v1/dashboard.py create mode 100644 backend/app/api/v1/observability.py create mode 100644 backend/app/api/v1/profile.py create mode 100644 backend/app/core/exception_handlers.py create mode 100644 backend/app/core/logging_config.py create mode 100644 backend/app/core/metrics.py create mode 100644 backend/app/core/request_context.py create mode 100644 backend/app/middleware/request_context.py create mode 100644 backend/app/services/draft_email.py create mode 100644 backend/app/services/ingest_resume.py create mode 100644 backend/app/services/job_text.py create mode 100644 backend/app/services/llm/safety.py create mode 100644 backend/app/services/tailor_orchestrator.py create mode 100644 backend/docs/ARCHITECTURE.md diff --git a/.env.example b/.env.example index 944b24b..259402d 100644 --- a/.env.example +++ b/.env.example @@ -48,8 +48,9 @@ AUTH_MODE=disabled # --- Agent / LLM --- # Local: AGENT_MODE=stub (no external calls). Deployed: AGENT_MODE=llm. +# `services/langgraph/workflow.py` (legacy apply workflow) uses the same vars via LangChain ChatOpenAI at {LLM_BASE_URL}/v1. AGENT_MODE=stub -# OpenAI-compatible base URL. For OpenRouter, you might use https://openrouter.ai/api +# OpenAI-compatible base URL. For OpenRouter use https://openrouter.ai/api (no trailing /v1) LLM_BASE_URL=https://api.openai.com # LLM_API_KEY=... # preferred # OPENROUTER_API_KEY=... # accepted alias @@ -60,3 +61,13 @@ LLM_BASE_URL=https://api.openai.com # OpenRouter optional headers (recommended) # OPENROUTER_REFERER=https://your-app.example # OPENROUTER_TITLE=TalentStreamAI + +# --- Observability (FastAPI) --- +# LOG_LEVEL=INFO +# LOG_JSON=false +# Set true in production for one JSON log line per event +# LOG_JSON=true +# ENABLE_PROMETHEUS=true +# SERVICE_NAME=talentstreamai-api +# Optional: OpenTelemetry gRPC/HTTP endpoint (set when you add otel packages) +# OTEL_EXPORTER_OTLP_ENDPOINT= diff --git a/backend/app/api/router.py b/backend/app/api/router.py index 4cda2b2..ae5f87f 100644 --- a/backend/app/api/router.py +++ b/backend/app/api/router.py @@ -1,10 +1,24 @@ from fastapi import APIRouter -from app.api.v1 import auth, generation, health, job_descriptions, resumes +from app.api.v1 import ( + applications, + auth, + dashboard, + generation, + health, + job_descriptions, + observability, + profile, + resumes, +) api_router = APIRouter() api_router.include_router(health.router, prefix="/v1", tags=["health"]) +api_router.include_router(observability.router, prefix="/v1", tags=["observability"]) api_router.include_router(auth.router, prefix="/v1/auth", tags=["auth"]) +api_router.include_router(profile.router, prefix="/v1", tags=["profile"]) +api_router.include_router(dashboard.router, prefix="/v1", tags=["dashboard"]) +api_router.include_router(applications.router, prefix="/v1", tags=["applications"]) api_router.include_router(resumes.router, prefix="/v1", tags=["resumes"]) api_router.include_router(job_descriptions.router, prefix="/v1", tags=["job_descriptions"]) api_router.include_router(generation.router, prefix="/v1", tags=["generation"]) diff --git a/backend/app/api/schemas/frontend.py b/backend/app/api/schemas/frontend.py new file mode 100644 index 0000000..d3f4a79 --- /dev/null +++ b/backend/app/api/schemas/frontend.py @@ -0,0 +1,207 @@ +"""Pydantic models aligned with the Next.js `src/lib/types.ts` (camelCase JSON).""" + +from __future__ import annotations + +from typing import Any + +from pydantic import BaseModel, ConfigDict, Field, model_validator +from pydantic.alias_generators import to_camel + +from app.core.db import ApplicationRecord, StoredDocument, UserProfile + + +def _cc() -> ConfigDict: + return ConfigDict( + populate_by_name=True, + alias_generator=to_camel, + ) + + +class ProfileOut(BaseModel): + model_config = _cc() + id: str + full_name: str + email: str + headline: str | None = None + base_resume_id: str | None = None + created_at: str + + +class ResumeOut(BaseModel): + model_config = _cc() + id: str + title: str + content: str + application_id: str | None = None + is_base: bool | None = None + created_at: str + + +class DashboardStatsOut(BaseModel): + model_config = _cc() + applications: int + interviews: int + average_match_score: float + resumes_generated: int + + +class GapItemOut(BaseModel): + model_config = _cc() + skill: str + severity: str + note: str | None = None + + +class ApplicationOut(BaseModel): + model_config = _cc() + id: str + company: str + position: str + job_url: str | None = None + job_description: str + match_score: int + status: str + resume_id: str | None = None + cover_letter: str | None = None + gaps: list[GapItemOut] | None = None + created_at: str + + +class MatchAnalysisOut(BaseModel): + model_config = _cc() + original_score: float + tailored_score: float + improvement: float + what_we_improved: list[str] = Field(default_factory=list) + strengths: list[str] = Field(default_factory=list) + remaining_deficits: list[str] = Field(default_factory=list) + matched_keywords: list[str] = Field(default_factory=list) + missing_keywords: list[str] = Field(default_factory=list) + suggestions: list[str] = Field(default_factory=list) + + +class DraftEmailOut(BaseModel): + model_config = _cc() + subject: str + body: str + + +class TailorRequestIn(BaseModel): + model_config = _cc() + base_resume_id: str + job_url: str | None = None + job_description: str | None = None + + @model_validator(mode="after") + def require_job(self) -> TailorRequestIn: + url = (self.job_url or "").strip() + desc = (self.job_description or "").strip() + if not url and len(desc) < 40: + raise ValueError("Provide a jobUrl or at least 40 characters of jobDescription") + if url and not url.lower().startswith(("http://", "https://")): + raise ValueError("jobUrl must be an http(s) URL") + return self + + +class TailorResponseOut(BaseModel): + model_config = _cc() + application_id: str + match_score: int + resume: ResumeOut + cover_letter: str + draft_email: DraftEmailOut + gaps: list[GapItemOut] + analysis: MatchAnalysisOut + + +def _gap_items(raw: list[Any]) -> list[GapItemOut]: + out: list[GapItemOut] = [] + for g in raw or []: + if isinstance(g, dict): + out.append( + GapItemOut( + skill=str(g.get("skill", "")), + severity=str(g.get("severity", "medium")), + note=g.get("note"), + ) + ) + return out + + +def map_profile(user_id: str, profile: UserProfile | None, claims: dict[str, Any]) -> ProfileOut: + email = (profile and profile.email) or str(claims.get("email") or "unknown@user.local") + name = (profile and profile.full_name) or str(claims.get("name") or "User") + # Stable until a profile row exists (avoids a new createdAt on every request). + cr = (profile and profile.created_at) or "2020-01-01T00:00:00+00:00" + return ProfileOut( + id=user_id, + full_name=name, + email=email, + headline=(profile and profile.headline) or None, + base_resume_id=(profile and profile.base_resume_id) or None, + created_at=cr, + ) + + +def map_resume( + doc: StoredDocument, *, is_base: bool, application_id: str | None +) -> ResumeOut: + title = str(doc.meta.get("title") or doc.filename or "Resume") + is_b = bool(doc.meta.get("is_base")) or is_base + return ResumeOut( + id=doc.id, + title=title[:500], + content=doc.text, + application_id=doc.meta.get("application_id") or application_id, + is_base=is_b, + created_at=doc.created_at, + ) + + +def map_application( + a: ApplicationRecord, *, list_view: bool = False +) -> ApplicationOut: + met = a.meta or {} + gaps = _gap_items(met.get("gaps", [])) + jdesc = a.job_description + if list_view and len(jdesc) > 2000: + jdesc = jdesc[:2000] + "…" + return ApplicationOut( + id=a.id, + company=str(a.company or "—"), + position=str(a.position or "—"), + job_url=a.job_url, + job_description=jdesc, + match_score=int(round(a.match_score)), + status=a.status, + resume_id=a.resume_id, + cover_letter=a.cover_letter, + gaps=gaps, + created_at=a.created_at, + ) + + +def map_match_analysis(m: dict[str, Any]) -> MatchAnalysisOut: + return MatchAnalysisOut( + original_score=float( + m.get("originalScore", m.get("original_score", 0)) or 0 + ), + tailored_score=float( + m.get("tailoredScore", m.get("tailored_score", 0)) or 0 + ), + improvement=float(m.get("improvement", 0) or 0), + what_we_improved=list( + m.get("whatWeImproved") or m.get("what_we_improved") or [] + ), + strengths=list(m.get("strengths") or []), + remaining_deficits=list( + m.get("remainingDeficits") or m.get("remaining_deficits") or [] + ), + matched_keywords=list( + m.get("matchedKeywords") or m.get("matched_keywords") or [] + ), + missing_keywords=list( + m.get("missingKeywords") or m.get("missing_keywords") or [] + ), + suggestions=list(m.get("suggestions") or []), + ) diff --git a/backend/app/api/v1/applications.py b/backend/app/api/v1/applications.py new file mode 100644 index 0000000..f2666b9 --- /dev/null +++ b/backend/app/api/v1/applications.py @@ -0,0 +1,88 @@ +from __future__ import annotations + +import structlog +from fastapi import APIRouter, Depends, HTTPException + +from app.api.schemas.frontend import ( + ApplicationOut, + DraftEmailOut, + GapItemOut, + TailorRequestIn, + TailorResponseOut, + map_application, + map_match_analysis, + map_resume, +) +from app.core.auth import AuthenticatedUser, get_current_user +from app.core.db import get_application, list_applications +from app.services.tailor_orchestrator import run_tailor_for_user + +router = APIRouter() +log = structlog.get_logger(__name__) + + +@router.get("/applications", response_model=list[ApplicationOut]) +def list_user_applications( + user: AuthenticatedUser = Depends(get_current_user), +) -> list[ApplicationOut]: + apps = list_applications(user_id=user.user_id) + return [map_application(a, list_view=True) for a in apps] + + +@router.get("/applications/{application_id}", response_model=ApplicationOut) +def get_one_application( + application_id: str, + user: AuthenticatedUser = Depends(get_current_user), +) -> ApplicationOut: + a = get_application(app_id=application_id, user_id=user.user_id) + if not a: + raise HTTPException(status_code=404, detail="Application not found") + return map_application(a, list_view=False) + + +@router.post("/applications/tailor", response_model=TailorResponseOut) +async def tailor_application( + body: TailorRequestIn, + user: AuthenticatedUser = Depends(get_current_user), +) -> TailorResponseOut: + try: + app_rec, _tailored, pl = await run_tailor_for_user( + user_id=user.user_id, + base_resume_id=body.base_resume_id, + job_url=body.job_url, + job_description=body.job_description, + ) + except ValueError as e: + log.info("tailor_rejected", reason=str(e)) + raise HTTPException(status_code=400, detail=str(e)) from e + except Exception as e: + log.exception("tailor_unexpected_error") + raise HTTPException( + status_code=500, detail="Tailor failed. Support has been notified." + ) from e + + tdoc = pl["tailored"] + gap_items = [ + GapItemOut( + skill=str(x.get("skill", "")), + severity=str(x.get("severity", "medium")), + note=x.get("note"), + ) + for x in (pl.get("gaps") or []) + ] + de = pl.get("draft_email") or {"subject": "Application", "body": ""} + return TailorResponseOut( + application_id=app_rec.id, + match_score=int(pl["match_score"]), + resume=map_resume( + tdoc, + is_base=bool(tdoc.meta.get("is_base", False)), + application_id=app_rec.id, + ), + cover_letter=pl["cover_letter"], + draft_email=DraftEmailOut( + subject=de.get("subject", "Application"), body=de.get("body", "") + ), + gaps=gap_items, + analysis=map_match_analysis(pl["analysis"]), + ) diff --git a/backend/app/api/v1/dashboard.py b/backend/app/api/v1/dashboard.py new file mode 100644 index 0000000..e16ba2e --- /dev/null +++ b/backend/app/api/v1/dashboard.py @@ -0,0 +1,22 @@ +from __future__ import annotations + +from fastapi import APIRouter, Depends + +from app.api.schemas.frontend import DashboardStatsOut +from app.core.auth import AuthenticatedUser, get_current_user +from app.core.db import dashboard_aggregates + +router = APIRouter() + + +@router.get("/dashboard/stats", response_model=DashboardStatsOut) +def get_dashboard_stats( + user: AuthenticatedUser = Depends(get_current_user), +) -> DashboardStatsOut: + d = dashboard_aggregates(user_id=user.user_id) + return DashboardStatsOut( + applications=int(d["applications"]), + interviews=int(d["interviews"]), + average_match_score=round(float(d["average_match_score"]), 1), + resumes_generated=int(d["resumes_generated"]), + ) diff --git a/backend/app/api/v1/observability.py b/backend/app/api/v1/observability.py new file mode 100644 index 0000000..e5c4872 --- /dev/null +++ b/backend/app/api/v1/observability.py @@ -0,0 +1,36 @@ +"""Health, readiness, and Prometheus metrics (when enabled).""" + +from __future__ import annotations + +from fastapi import APIRouter, Response +from fastapi.responses import PlainTextResponse + +from app.core import metrics +from app.core.config import settings +from app.core.db import get_conn + +router = APIRouter() + + +@router.get("/ready", tags=["health"]) +def ready() -> dict[str, str]: + """Readiness: verify DB connectivity (swap for deep checks in k8s).""" + try: + conn = get_conn() + try: + conn.execute("SELECT 1") + finally: + conn.close() + except Exception as e: + return {"status": "not_ready", "reason": f"db: {e}"} + return {"status": "ready"} + + +@router.get("/metrics", include_in_schema=False) +def prometheus_metrics() -> Response: + if not settings.enable_prometheus: + return Response(status_code=404) + return PlainTextResponse( + content=metrics.metrics_payload().decode("utf-8"), + media_type="text/plain; version=0.0.4; charset=utf-8", + ) diff --git a/backend/app/api/v1/profile.py b/backend/app/api/v1/profile.py new file mode 100644 index 0000000..08a6a14 --- /dev/null +++ b/backend/app/api/v1/profile.py @@ -0,0 +1,39 @@ +from __future__ import annotations + +import structlog +from fastapi import APIRouter, Depends, File, HTTPException, UploadFile + +from app.api.schemas.frontend import ProfileOut, ResumeOut, map_profile, map_resume +from app.core.auth import AuthenticatedUser, get_current_user +from app.core.db import get_user_profile +from app.services.ingest_resume import ingest_uploaded_resume + +router = APIRouter() +log = structlog.get_logger(__name__) + + +@router.get("/profile", response_model=ProfileOut) +def get_profile(user: AuthenticatedUser = Depends(get_current_user)) -> ProfileOut: + p = get_user_profile(user_id=user.user_id) + return map_profile(user.user_id, p, user.claims) + + +@router.post("/profile/base-resume", response_model=ResumeOut) +async def upload_base_resume( + file: UploadFile = File(...), + user: AuthenticatedUser = Depends(get_current_user), +) -> ResumeOut: + try: + res = await ingest_uploaded_resume( + file=file, user=user, set_as_base=True + ) + except HTTPException: + raise + except Exception as e: + log.exception("base_resume_upload_failed") + raise HTTPException(status_code=500, detail="Failed to store resume") from e + p = get_user_profile(user_id=user.user_id) + is_base = bool(p and p.base_resume_id == res.document.id) + return map_resume( + res.document, is_base=is_base, application_id=None + ) diff --git a/backend/app/api/v1/resumes.py b/backend/app/api/v1/resumes.py index 42b370c..13284bd 100644 --- a/backend/app/api/v1/resumes.py +++ b/backend/app/api/v1/resumes.py @@ -1,93 +1,64 @@ from __future__ import annotations -import logging - +import structlog from fastapi import APIRouter, Depends, File, HTTPException, UploadFile -from starlette.concurrency import run_in_threadpool +from app.api.schemas.frontend import ResumeOut, map_resume from app.core.auth import AuthenticatedUser, get_current_user -from app.core.config import settings -from app.core.db import create_document, get_document -from app.services.text_guardrails import normalize_user_text -from app.services.uploads import delete_saved_upload, extract_text, save_upload, validate_upload +from app.core.db import get_document, get_user_profile, list_documents +from app.services.ingest_resume import ingest_uploaded_resume router = APIRouter() -logger = logging.getLogger(__name__) +log = structlog.get_logger(__name__) -@router.post("/resumes") -async def upload_resume( - file: UploadFile = File(...), +@router.get("/resumes", response_model=list[ResumeOut]) +def list_resumes( user: AuthenticatedUser = Depends(get_current_user), -) -> dict[str, str]: - try: - chunks: list[bytes] = [] - total = 0 - while True: - chunk = await file.read(1024 * 1024) - if not chunk: - break - total += len(chunk) - if total > settings.max_upload_bytes: - raise HTTPException(status_code=413, detail="File too large") - chunks.append(chunk) - raw = b"".join(chunks) - - def _process(): - detected_type = validate_upload(filename=file.filename or "", content_type=file.content_type, data=raw) - extracted = extract_text(detected_type=detected_type, data=raw) - extracted = normalize_user_text(extracted) - if not extracted: - return None, detected_type, "" - - saved = save_upload( - detected_type=detected_type, - owner_user_id=user.user_id, - content_type=file.content_type, - data=raw, - ) - return saved, detected_type, extracted - - saved, detected_type, extracted = await run_in_threadpool(_process) - if not extracted: - raise HTTPException(status_code=400, detail="Could not extract text from resume") - try: - doc = await run_in_threadpool( - create_document, - kind="resume", - owner_user_id=user.user_id, - text=extracted, - filename=file.filename, - content_type=file.content_type, - file_path=saved.path if saved else None, - meta={"bytes": len(raw), "detected_type": detected_type}, - ) - except Exception: - try: - await run_in_threadpool(delete_saved_upload, saved.path if saved else None) - except Exception: - logger.exception("Failed to clean up uploaded resume after DB insert failure") - raise - return {"resume_id": doc.id} - except HTTPException: - raise - except ValueError as e: - raise HTTPException(status_code=400, detail=str(e)) from e - except RuntimeError as e: - raise HTTPException(status_code=500, detail=str(e)) from e +) -> list[ResumeOut]: + p = get_user_profile(user_id=user.user_id) + base_id = p.base_resume_id if p else None + docs = list_documents(owner_user_id=user.user_id, kind="resume") + out: list[ResumeOut] = [] + for d in docs: + is_base = base_id is not None and d.id == base_id + out.append(map_resume(d, is_base=is_base, application_id=d.meta.get("application_id"))) + return out -@router.get("/resumes/{resume_id}") +@router.get("/resumes/{resume_id}", response_model=ResumeOut) def get_resume( resume_id: str, user: AuthenticatedUser = Depends(get_current_user), -) -> dict[str, str | None]: +) -> ResumeOut: + p = get_user_profile(user_id=user.user_id) + base_id = p.base_resume_id if p else None doc = get_document(doc_id=resume_id, owner_user_id=user.user_id) if not doc or doc.kind != "resume": raise HTTPException(status_code=404, detail="Resume not found") - return { - "resume_id": doc.id, - "filename": doc.filename, - "content_type": doc.content_type, - "created_at": doc.created_at, - } + is_base = base_id is not None and doc.id == base_id + return map_resume( + doc, is_base=is_base, application_id=doc.meta.get("application_id") + ) + + +@router.post("/resumes", response_model=ResumeOut) +async def upload_resume( + file: UploadFile = File(...), + user: AuthenticatedUser = Depends(get_current_user), +) -> ResumeOut: + try: + res = await ingest_uploaded_resume( + file=file, user=user, set_as_base=False + ) + except HTTPException: + raise + except Exception as e: + log.exception("resume_upload_failed") + raise HTTPException(status_code=500, detail="Failed to store resume") from e + p = get_user_profile(user_id=user.user_id) + base_id = p.base_resume_id if p else None + is_base = base_id is not None and res.document.id == base_id + return map_resume( + res.document, is_base=is_base, application_id=None + ) diff --git a/backend/app/core/auth.py b/backend/app/core/auth.py index a6c7c90..fe2b18e 100644 --- a/backend/app/core/auth.py +++ b/backend/app/core/auth.py @@ -3,6 +3,7 @@ from dataclasses import dataclass from typing import Any +import structlog from fastapi import Depends, HTTPException from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer @@ -24,7 +25,9 @@ def get_current_user( credentials: HTTPAuthorizationCredentials | None = Depends(_bearer), ) -> AuthenticatedUser: if settings.auth_mode == "disabled": - return AuthenticatedUser(user_id="anonymous", claims={"auth_mode": "disabled"}) + u = AuthenticatedUser(user_id="anonymous", claims={"auth_mode": "disabled"}) + structlog.contextvars.bind_contextvars(user_id=u.user_id) + return u if settings.auth_mode != "clerk_jwks": raise HTTPException(status_code=500, detail="Unsupported AUTH_MODE configuration") @@ -42,4 +45,6 @@ def get_current_user( if not user_id: raise HTTPException(status_code=401, detail="Invalid token (missing subject)") - return AuthenticatedUser(user_id=user_id, claims=claims) + u = AuthenticatedUser(user_id=user_id, claims=claims) + structlog.contextvars.bind_contextvars(user_id=u.user_id) + return u diff --git a/backend/app/core/config.py b/backend/app/core/config.py index 85e170b..2b21418 100644 --- a/backend/app/core/config.py +++ b/backend/app/core/config.py @@ -54,6 +54,15 @@ class Settings(BaseSettings): openrouter_referer: str | None = None openrouter_title: str | None = None + # --- Observability --- + log_level: str = "INFO" + log_json: bool = False + enable_prometheus: bool = True + request_id_header: str = "X-Request-Id" + # Set to enable OpenTelemetry gRPC/HTTP export (requires optional otel packages) + otel_exporter_otlp_endpoint: str | None = None + service_name: str = "talentstreamai-api" + @property def cors_origins_list(self) -> list[str]: return [ diff --git a/backend/app/core/db.py b/backend/app/core/db.py index 97e66fa..4e4f9fa 100644 --- a/backend/app/core/db.py +++ b/backend/app/core/db.py @@ -49,6 +49,40 @@ def init_db() -> None: ) conn.execute("CREATE INDEX IF NOT EXISTS idx_documents_owner ON documents(owner_user_id)") conn.execute("CREATE INDEX IF NOT EXISTS idx_documents_kind ON documents(kind)") + conn.execute( + """ + CREATE TABLE IF NOT EXISTS user_profiles ( + user_id TEXT PRIMARY KEY, + email TEXT, + full_name TEXT, + headline TEXT, + base_resume_id TEXT, + created_at TEXT NOT NULL, + updated_at TEXT NOT NULL + ) + """ + ) + conn.execute( + """ + CREATE TABLE IF NOT EXISTS application_records ( + id TEXT PRIMARY KEY, + user_id TEXT NOT NULL, + company TEXT, + position TEXT, + job_url TEXT, + job_description TEXT NOT NULL, + match_score REAL NOT NULL DEFAULT 0, + status TEXT NOT NULL DEFAULT 'draft', + base_resume_id TEXT, + resume_id TEXT, + cover_letter TEXT, + meta_json TEXT NOT NULL, + created_at TEXT NOT NULL + ) + """ + ) + conn.execute("CREATE INDEX IF NOT EXISTS idx_app_records_user ON application_records(user_id)") + conn.execute("CREATE INDEX IF NOT EXISTS idx_app_records_created ON application_records(created_at)") conn.commit() finally: conn.close() @@ -133,3 +167,304 @@ def get_document(*, doc_id: str, owner_user_id: str) -> StoredDocument | None: created_at=row["created_at"], meta=meta, ) + + +def list_documents( + *, owner_user_id: str, kind: str | None = None, limit: int = 200 +) -> list[StoredDocument]: + """List documents for a user, newest first.""" + conn = get_conn() + try: + if kind: + rows = conn.execute( + """ + SELECT * FROM documents + WHERE owner_user_id = ? AND kind = ? + ORDER BY created_at DESC + LIMIT ? + """, + (owner_user_id, kind, limit), + ).fetchall() + else: + rows = conn.execute( + """ + SELECT * FROM documents + WHERE owner_user_id = ? + ORDER BY created_at DESC + LIMIT ? + """, + (owner_user_id, limit), + ).fetchall() + finally: + conn.close() + + out: list[StoredDocument] = [] + for row in rows: + meta = json.loads(row["meta_json"]) if row["meta_json"] else {} + out.append( + StoredDocument( + id=row["id"], + kind=row["kind"], + owner_user_id=row["owner_user_id"], + filename=row["filename"], + content_type=row["content_type"], + file_path=row["file_path"], + text=row["text"], + created_at=row["created_at"], + meta=meta, + ) + ) + return out + + +@dataclass(frozen=True) +class UserProfile: + user_id: str + email: str | None + full_name: str | None + headline: str | None + base_resume_id: str | None + created_at: str + updated_at: str + + +def get_user_profile(*, user_id: str) -> UserProfile | None: + conn = get_conn() + try: + row = conn.execute( + "SELECT * FROM user_profiles WHERE user_id = ?", + (user_id,), + ).fetchone() + finally: + conn.close() + if not row: + return None + return UserProfile( + user_id=row["user_id"], + email=row["email"], + full_name=row["full_name"], + headline=row["headline"], + base_resume_id=row["base_resume_id"], + created_at=row["created_at"], + updated_at=row["updated_at"], + ) + + +def upsert_user_profile( + *, + user_id: str, + email: str | None = None, + full_name: str | None = None, + headline: str | None = None, + base_resume_id: str | None = None, +) -> UserProfile: + now = datetime.now(UTC).isoformat() + existing = get_user_profile(user_id=user_id) + conn = get_conn() + try: + if existing is None: + conn.execute( + """ + INSERT INTO user_profiles + (user_id, email, full_name, headline, base_resume_id, created_at, updated_at) + VALUES (?, ?, ?, ?, ?, ?, ?) + """, + (user_id, email, full_name, headline, base_resume_id, now, now), + ) + else: + conn.execute( + """ + UPDATE user_profiles + SET email = COALESCE(?, email), + full_name = COALESCE(?, full_name), + headline = COALESCE(?, headline), + base_resume_id = COALESCE(?, base_resume_id), + updated_at = ? + WHERE user_id = ? + """, + (email, full_name, headline, base_resume_id, now, user_id), + ) + conn.commit() + finally: + conn.close() + p = get_user_profile(user_id=user_id) + assert p is not None + return p + + +@dataclass(frozen=True) +class ApplicationRecord: + id: str + user_id: str + company: str | None + position: str | None + job_url: str | None + job_description: str + match_score: float + status: str + base_resume_id: str | None + resume_id: str | None + cover_letter: str | None + meta: dict[str, Any] + created_at: str + + +def create_application( + *, + user_id: str, + company: str | None, + position: str | None, + job_url: str | None, + job_description: str, + match_score: float, + status: str, + base_resume_id: str | None, + resume_id: str | None, + cover_letter: str | None, + meta: dict[str, Any] | None = None, +) -> ApplicationRecord: + app_id = str(uuid4()) + created_at = datetime.now(UTC).isoformat() + meta_json = json.dumps(meta or {}, ensure_ascii=True) + conn = get_conn() + try: + conn.execute( + """ + INSERT INTO application_records ( + id, user_id, company, position, job_url, job_description, + match_score, status, base_resume_id, resume_id, cover_letter, meta_json, created_at + ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?) + """, + ( + app_id, + user_id, + company, + position, + job_url, + job_description, + match_score, + status, + base_resume_id, + resume_id, + cover_letter, + meta_json, + created_at, + ), + ) + conn.commit() + finally: + conn.close() + r = get_application(app_id=app_id, user_id=user_id) + assert r is not None + return r + + +def get_application(*, app_id: str, user_id: str) -> ApplicationRecord | None: + conn = get_conn() + try: + row = conn.execute( + """ + SELECT * FROM application_records + WHERE id = ? AND user_id = ? LIMIT 1 + """, + (app_id, user_id), + ).fetchone() + finally: + conn.close() + if not row: + return None + return _row_to_application(row) + + +def list_applications( + *, user_id: str, limit: int = 100 +) -> list[ApplicationRecord]: + conn = get_conn() + try: + rows = conn.execute( + """ + SELECT * FROM application_records + WHERE user_id = ? + ORDER BY created_at DESC + LIMIT ? + """, + (user_id, limit), + ).fetchall() + finally: + conn.close() + return [_row_to_application(r) for r in rows] + + +def _row_to_application(row: sqlite3.Row) -> ApplicationRecord: + raw = row["meta_json"] or "{}" + meta: dict[str, Any] = json.loads(raw) if raw else {} + return ApplicationRecord( + id=row["id"], + user_id=row["user_id"], + company=row["company"], + position=row["position"], + job_url=row["job_url"], + job_description=row["job_description"], + match_score=float(row["match_score"] or 0), + status=row["status"] or "draft", + base_resume_id=row["base_resume_id"], + resume_id=row["resume_id"], + cover_letter=row["cover_letter"], + meta=meta, + created_at=row["created_at"], + ) + + +def update_document_meta( + *, doc_id: str, owner_user_id: str, meta_patch: dict[str, Any] +) -> StoredDocument | None: + """Merge meta_patch into the document's meta JSON.""" + doc = get_document(doc_id=doc_id, owner_user_id=owner_user_id) + if not doc: + return None + merged = {**doc.meta, **meta_patch} + meta_json = json.dumps(merged, ensure_ascii=True) + conn = get_conn() + try: + conn.execute( + "UPDATE documents SET meta_json = ? WHERE id = ? AND owner_user_id = ?", + (meta_json, doc_id, owner_user_id), + ) + conn.commit() + finally: + conn.close() + return get_document(doc_id=doc_id, owner_user_id=owner_user_id) + + +def dashboard_aggregates(*, user_id: str) -> dict[str, int | float]: + """Pre-computed dashboard numbers for a user (SQLite; swap for warehouse in prod).""" + conn = get_conn() + try: + n_apps = conn.execute( + "SELECT COUNT(*) AS c FROM application_records WHERE user_id = ?", + (user_id,), + ).fetchone()["c"] + n_interview = conn.execute( + "SELECT COUNT(*) AS c FROM application_records WHERE user_id = ? AND status = 'interview'", + (user_id,), + ).fetchone()["c"] + score_row = conn.execute( + """ + SELECT AVG(match_score) AS a FROM application_records + WHERE user_id = ? AND match_score > 0 + """, + (user_id,), + ).fetchone() + avg = score_row["a"] if score_row and score_row["a"] is not None else 0.0 + n_tailored = conn.execute( + "SELECT COUNT(*) AS c FROM documents WHERE owner_user_id = ? AND kind = 'resume'", + (user_id,), + ).fetchone()["c"] + finally: + conn.close() + return { + "applications": int(n_apps), + "interviews": int(n_interview), + "average_match_score": float(avg) if avg else 0.0, + "resumes_generated": int(n_tailored), + } diff --git a/backend/app/core/exception_handlers.py b/backend/app/core/exception_handlers.py new file mode 100644 index 0000000..69c06a4 --- /dev/null +++ b/backend/app/core/exception_handlers.py @@ -0,0 +1,35 @@ +"""Consistent error bodies with traceable request ids for unexpected failures.""" + +from __future__ import annotations + +import uuid +from typing import Any + +import structlog +from fastapi import Request +from fastapi.exception_handlers import ( + http_exception_handler, + request_validation_exception_handler, +) +from fastapi.exceptions import RequestValidationError +from fastapi.responses import JSONResponse +from starlette.exceptions import HTTPException as StarletteHTTPException + +log = structlog.get_logger(__name__) + + +async def global_exception_handler(request: Request, exc: Exception) -> JSONResponse: + if isinstance(exc, RequestValidationError): + return await request_validation_exception_handler(request, exc) + if isinstance(exc, StarletteHTTPException): + return await http_exception_handler(request, exc) + err_id = str(uuid.uuid4()) + log.exception("unhandled_exception", error_id=err_id, path=request.url.path) + body: dict[str, Any] = { + "detail": "An internal error occurred.", + "errorId": err_id, + } + rid = request.headers.get("X-Request-Id") + if rid: + body["requestId"] = rid + return JSONResponse(status_code=500, content=body) diff --git a/backend/app/core/logging_config.py b/backend/app/core/logging_config.py new file mode 100644 index 0000000..76a8952 --- /dev/null +++ b/backend/app/core/logging_config.py @@ -0,0 +1,43 @@ +"""Structured logging: JSON (production) or console (local).""" + +from __future__ import annotations + +import logging +import sys + +import structlog + +from app.core.config import settings + + +def configure_logging() -> None: + level = getattr(logging, settings.log_level.upper(), logging.INFO) + timestamper = structlog.processors.TimeStamper(fmt="iso", utc=True) + shared: list[structlog.types.Processor] = [ + structlog.contextvars.merge_contextvars, + structlog.processors.add_log_level, + structlog.dev.set_exc_info, + ] + if settings.log_json: + processors: list[structlog.types.Processor] = [ + *shared, + timestamper, + structlog.processors.dict_tracebacks, + structlog.processors.JSONRenderer(), + ] + else: + processors = [ + *shared, + timestamper, + structlog.dev.ConsoleRenderer(colors=sys.stderr.isatty()), + ] + + structlog.configure( + processors=processors, + logger_factory=structlog.PrintLoggerFactory(), + cache_logger_on_first_use=True, + ) + root = logging.getLogger() + root.setLevel(level) + for name in ("httpx", "httpcore", "uvicorn", "uvicorn.error"): + logging.getLogger(name).setLevel(logging.WARNING) diff --git a/backend/app/core/metrics.py b/backend/app/core/metrics.py new file mode 100644 index 0000000..ca62046 --- /dev/null +++ b/backend/app/core/metrics.py @@ -0,0 +1,43 @@ +"""Prometheus metrics (exposed at /api/v1/metrics when enabled).""" + +from __future__ import annotations + +from prometheus_client import Counter, Histogram, generate_latest, REGISTRY + +# HTTP +http_requests = Counter( + "http_requests_total", + "Total HTTP requests", + ("method", "path_template", "status"), +) +http_request_latency = Histogram( + "http_request_duration_seconds", + "Request latency in seconds", + ("method", "path_template"), + buckets=(0.01, 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0, 30.0, 60.0), +) + +# LLM +llm_calls = Counter( + "llm_invocations_total", + "LLM API calls", + ("model", "outcome"), +) +llm_tokens = Counter( + "llm_tokens_total", + "Token usage (when reported by the provider)", + ("model", "token_type"), +) +llm_latency = Histogram( + "llm_request_duration_seconds", + "LLM request duration", + ("model",), + buckets=(0.1, 0.25, 0.5, 1, 2, 5, 10, 30, 60, 120), +) + +# Domain +tailor_runs = Counter("tailor_runs_total", "Resume tailor runs", ("outcome",)) + + +def metrics_payload() -> bytes: + return generate_latest(REGISTRY) diff --git a/backend/app/core/request_context.py b/backend/app/core/request_context.py new file mode 100644 index 0000000..e66816e --- /dev/null +++ b/backend/app/core/request_context.py @@ -0,0 +1,47 @@ +"""Request-scoped context (traceability without threading globals).""" + +from __future__ import annotations + +import contextvars +import uuid +from typing import Any + +_request_id: contextvars.ContextVar[str | None] = contextvars.ContextVar("request_id", default=None) +_user_id: contextvars.ContextVar[str | None] = contextvars.ContextVar("user_id", default=None) + + +def get_request_id() -> str | None: + return _request_id.get() + + +def set_request_id(value: str | None) -> contextvars.Token[str | None]: + return _request_id.set(value) + + +def reset_request_id(token: contextvars.Token[str | None]) -> None: + _request_id.reset(token) + + +def new_request_id() -> str: + return str(uuid.uuid4()) + + +def get_context_user_id() -> str | None: + return _user_id.get() + + +def set_user_id(value: str | None) -> contextvars.Token[str | None]: + return _user_id.set(value) + + +def reset_user_id(token: contextvars.Token[str | None]) -> None: + _user_id.reset(token) + + +def context_bind() -> dict[str, Any]: + out: dict[str, Any] = {} + if rid := get_request_id(): + out["request_id"] = rid + if uid := get_context_user_id(): + out["user_id"] = uid + return out diff --git a/backend/app/main.py b/backend/app/main.py index a09a023..d8f8555 100644 --- a/backend/app/main.py +++ b/backend/app/main.py @@ -1,22 +1,33 @@ import os +import structlog from fastapi import FastAPI from fastapi.middleware.cors import CORSMiddleware from app.api.router import api_router from app.core.config import settings from app.core.db import init_db +from app.core.exception_handlers import global_exception_handler +from app.core.logging_config import configure_logging +from app.middleware.request_context import RequestContextMiddleware from app.services.llm.client import close_llm_http_clients +configure_logging() +slog = structlog.get_logger(__name__) + app = FastAPI( title="TalentStreamAI API", version="0.1.0", - description="Backend service for the TalentStreamAI capstone (FastAPI + future LangGraph agents).", + description="Backend service for the TalentStreamAI (FastAPI, LangGraph, observability).", ) +app.add_exception_handler(Exception, global_exception_handler) + + @app.on_event("startup") def _startup() -> None: init_db() + slog.info("service_starting", environment=settings.deployment_environment or "local") def _running_in_aws() -> bool: return bool( @@ -64,7 +75,10 @@ async def _shutdown() -> None: allow_credentials=True, allow_methods=["*"], allow_headers=["*"], + expose_headers=[settings.request_id_header or "X-Request-Id"], ) +# Outermost: request id + structlog context (last added in Starlette). +app.add_middleware(RequestContextMiddleware) app.include_router(api_router, prefix="/api") diff --git a/backend/app/middleware/request_context.py b/backend/app/middleware/request_context.py new file mode 100644 index 0000000..05e3242 --- /dev/null +++ b/backend/app/middleware/request_context.py @@ -0,0 +1,59 @@ +"""Request ID propagation, structlog context, and HTTP metrics.""" + +from __future__ import annotations + +import time +from collections.abc import Awaitable, Callable + +from starlette.middleware.base import BaseHTTPMiddleware +from starlette.requests import Request +from starlette.responses import Response +from starlette.routing import Match + +from app.core.config import settings +from app.core import metrics +from app.core.request_context import new_request_id, reset_request_id, set_request_id + + +def _path_template(request: Request) -> str: + for route in request.app.routes: + match, _ = route.matches(request.scope) + if match == Match.FULL and hasattr(route, "path"): + return str(route.path) + return request.url.path + + +class RequestContextMiddleware(BaseHTTPMiddleware): + async def dispatch( + self, request: Request, call_next: Callable[[Request], Awaitable[Response]] + ) -> Response: + structlog.contextvars.clear_contextvars() + h = {k.lower(): v for k, v in request.headers.items()} + rid = h.get("x-request-id") or new_request_id() + tok = set_request_id(rid) + structlog.contextvars.bind_contextvars(request_id=rid) + path_t = _path_template(request) + structlog.contextvars.bind_contextvars(http_path=path_t, http_method=request.method) + t0 = time.perf_counter() + try: + response = await call_next(request) + except Exception: + dt = time.perf_counter() - t0 + if settings.enable_prometheus: + metrics.http_requests.labels( + request.method, path_t, "5xx" + ).inc() + metrics.http_request_latency.labels( + request.method, path_t + ).observe(dt) + # Full traceback: global exception handler + raise + dt = time.perf_counter() - t0 + if settings.enable_prometheus: + code = response.status_code + bucket = f"{code // 100}xx" + metrics.http_requests.labels(request.method, path_t, bucket).inc() + metrics.http_request_latency.labels(request.method, path_t).observe(dt) + response.headers["X-Request-Id"] = rid + reset_request_id(tok) + return response diff --git a/backend/app/services/draft_email.py b/backend/app/services/draft_email.py new file mode 100644 index 0000000..292c64d --- /dev/null +++ b/backend/app/services/draft_email.py @@ -0,0 +1,43 @@ +"""Parse model-generated application email drafts into a stable {subject, body} shape.""" + +from __future__ import annotations + +import re + + +def parse_draft_email(raw: str) -> dict[str, str]: + t = (raw or "").strip() + if not t: + return {"subject": "Application", "body": ""} + subject = "Application" + body = t + m = re.search(r"^\s*Subject:\s*(.+?)\s*$", t, re.IGNORECASE | re.MULTILINE) + if m: + subject = m.group(1).strip()[:200] + # Strip common prefixes from the remaining body + for pat in (r"^\s*Body:\s*", r"^\s*To:.*$"): + t = re.sub(pat, "", t, flags=re.IGNORECASE | re.MULTILINE) + lines = t.splitlines() + out: list[str] = [] + skip = True + for line in lines: + if re.match(r"^\s*Subject:\s*", line, re.IGNORECASE): + skip = True + continue + if re.match(r"^\s*Body:\s*", line, re.IGNORECASE): + skip = False + rest = re.sub(r"^\s*Body:\s*", "", line, flags=re.IGNORECASE) + if rest.strip(): + out.append(rest) + continue + if skip and not line.strip(): + continue + skip = False + out.append(line) + if out: + body = "\n".join(out).strip() or t + else: + body = t + if not body: + body = t + return {"subject": subject, "body": body} diff --git a/backend/app/services/ingest_resume.py b/backend/app/services/ingest_resume.py new file mode 100644 index 0000000..0b48980 --- /dev/null +++ b/backend/app/services/ingest_resume.py @@ -0,0 +1,106 @@ +"""Shared upload + text extraction for resume documents.""" + +from __future__ import annotations + +import logging +from dataclasses import dataclass +from typing import Any + +from fastapi import HTTPException, UploadFile +from starlette.concurrency import run_in_threadpool + +from app.core.auth import AuthenticatedUser +from app.core.config import settings +from app.core.db import StoredDocument, create_document, upsert_user_profile +from app.services.text_guardrails import normalize_user_text +from app.services.uploads import delete_saved_upload, extract_text, save_upload, validate_upload + +logger = logging.getLogger(__name__) + + +@dataclass(frozen=True) +class IngestResult: + document: StoredDocument + byte_size: int + + +async def ingest_uploaded_resume( + *, + file: UploadFile, + user: AuthenticatedUser, + set_as_base: bool, +) -> IngestResult: + """Parse upload, persist as a resume document, optionally mark as the user's base resume.""" + chunks: list[bytes] = [] + total = 0 + while True: + chunk = await file.read(1024 * 1024) + if not chunk: + break + total += len(chunk) + if total > settings.max_upload_bytes: + raise HTTPException(status_code=413, detail="File too large") + chunks.append(chunk) + raw = b"".join(chunks) + + def _process() -> tuple[Any, str, str]: + detected_type = validate_upload( + filename=file.filename or "", content_type=file.content_type, data=raw + ) + extracted = extract_text(detected_type=detected_type, data=raw) + extracted = normalize_user_text(extracted) + if not extracted: + return None, detected_type, "" + saved = save_upload( + detected_type=detected_type, + owner_user_id=user.user_id, + content_type=file.content_type, + data=raw, + ) + return saved, detected_type, extracted + + saved, detected_type, extracted = await run_in_threadpool(_process) + if not extracted: + raise HTTPException(status_code=400, detail="Could not extract text from resume") + + title = (file.filename or "Resume").rsplit("/")[-1][:200] + meta: dict[str, Any] = { + "bytes": len(raw), + "detected_type": detected_type, + "title": title, + "is_base": set_as_base, + } + try: + doc = await run_in_threadpool( + create_document, + kind="resume", + owner_user_id=user.user_id, + text=extracted, + filename=file.filename, + content_type=file.content_type, + file_path=saved.path if saved else None, + meta=meta, + ) + except Exception: + try: + await run_in_threadpool(delete_saved_upload, saved.path if saved else None) + except Exception: + logger.exception("Failed to clean up uploaded resume after DB insert failure") + raise + + if set_as_base: + email = str(user.claims.get("email") or "") or None + full_name = str( + user.claims.get("name") + or user.claims.get("given_name") + or "User" + ) + await run_in_threadpool( + upsert_user_profile, + user_id=user.user_id, + email=email, + full_name=full_name, + headline=None, + base_resume_id=doc.id, + ) + return IngestResult(document=doc, byte_size=len(raw)) diff --git a/backend/app/services/job_text.py b/backend/app/services/job_text.py new file mode 100644 index 0000000..3e89d13 --- /dev/null +++ b/backend/app/services/job_text.py @@ -0,0 +1,34 @@ +"""Turn structured job data (e.g. from the fetcher) into a single text block for the LLM.""" + +from __future__ import annotations + +from typing import Any + + +def job_data_to_text(job: dict[str, Any]) -> str: + if not job: + return "" + title = (job.get("title") or "").strip() + company = (job.get("company") or "").strip() + loc = (job.get("location") or "").strip() + url = (job.get("url") or "").strip() + desc = (job.get("description") or "").strip() + req = (job.get("requirements") or "").strip() + resp = (job.get("responsibilities") or "").strip() + ben = (job.get("benefits") or "").strip() + parts: list[str] = [] + if title or company: + parts.append(f"{title} at {company}".strip()) + if loc: + parts.append(f"Location: {loc}") + if url: + parts.append(f"Source URL: {url}") + for label, val in ( + ("Full description", desc), + ("Requirements", req), + ("Responsibilities", resp), + ("Benefits", ben), + ): + if val: + parts.append(f"{label}:\n{val}") + return "\n\n".join(parts) if parts else desc diff --git a/backend/app/services/langgraph/streaming_agent.py b/backend/app/services/langgraph/streaming_agent.py index 472c881..ca16fea 100644 --- a/backend/app/services/langgraph/streaming_agent.py +++ b/backend/app/services/langgraph/streaming_agent.py @@ -1,10 +1,12 @@ from __future__ import annotations import json +import time from collections import Counter from functools import lru_cache -from typing import Any +from typing import Any, cast +import structlog from langgraph.graph import END, StateGraph from typing_extensions import TypedDict @@ -221,6 +223,34 @@ def _sse(event: str, data: dict) -> str: return f"event: {event}\ndata: {payload}" +_log = structlog.get_logger(__name__) + + +async def run_tailor_pipeline( + *, resume_text: str, job_description_text: str +) -> dict[str, Any]: + """ + Non-streaming end-to-end: gap analysis, tailored resume, cover letter, email draft. + Reuses the same graph as :func:`stream_generation` for a single final state. + """ + app = _graph() + state: AgentState = { + "resume_text": resume_text, + "job_description_text": job_description_text, + } + t0 = time.perf_counter() + try: + out = await app.ainvoke(state) + except Exception: + _log.exception("tailor_pipeline_ainvoke_failed") + raise + _log.info( + "tailor_pipeline_complete", + duration_ms=round((time.perf_counter() - t0) * 1000, 2), + ) + return cast(dict[str, Any], out) + + def _cap(text: str) -> str: if len(text) <= settings.max_output_chars: return text diff --git a/backend/app/services/langgraph/workflow.py b/backend/app/services/langgraph/workflow.py index 55862a7..4d826e1 100644 --- a/backend/app/services/langgraph/workflow.py +++ b/backend/app/services/langgraph/workflow.py @@ -1,8 +1,7 @@ """Complete LangGraph workflow for TalentStreamAI with document generation.""" import os -from typing import Any -from typing import Optional +from typing import Any, Optional from langchain_openai import ChatOpenAI from langchain_core.messages import HumanMessage @@ -31,12 +30,45 @@ class TalentStreamState(BaseModel): error: Optional[str] = None -def _get_llm(): - """Get LLM client (uses OpenAI).""" - api_key = settings.openai_api_key or os.environ.get("OPENAI_API_KEY") - if api_key: - return ChatOpenAI(model="gpt-4o", api_key=api_key) - raise ValueError("No LLM API key configured (OPENAI_API_KEY)") +def _langchain_openai_base_url() -> str: + """ + `LLM_BASE_URL` matches `LlmClient` (no trailing /v1). ChatOpenAI expects the + full OpenAI-compatible root including /v1 (e.g. https://openrouter.ai/api/v1). + """ + raw = (settings.llm_base_url or "https://api.openai.com").rstrip("/") + if raw.endswith("/v1"): + return raw + return f"{raw}/v1" + + +def _get_llm() -> ChatOpenAI: + """OpenAI-compatible chat model (OpenAI, OpenRouter, or other /v1 hosts).""" + api_key = ( + settings.llm_api_key + or settings.openai_api_key + or os.environ.get("OPENAI_API_KEY") + ) + if not api_key: + raise ValueError( + "No LLM API key configured. Set LLM_API_KEY, OPENROUTER_API_KEY, or OPENAI_API_KEY.", + ) + + default_headers: dict[str, str] = {} + if settings.openrouter_referer: + default_headers["HTTP-Referer"] = settings.openrouter_referer + if settings.openrouter_title: + default_headers["X-Title"] = settings.openrouter_title + + params: dict[str, Any] = { + "model": settings.llm_model, + "api_key": api_key, + "base_url": _langchain_openai_base_url(), + "temperature": settings.llm_temperature, + "max_tokens": settings.llm_max_tokens, + } + if default_headers: + params["default_headers"] = default_headers + return ChatOpenAI(**params) def _generate_tailored_resume(state: TalentStreamState) -> TalentStreamState: diff --git a/backend/app/services/llm/client.py b/backend/app/services/llm/client.py index 9cfa33f..35dc5c5 100644 --- a/backend/app/services/llm/client.py +++ b/backend/app/services/llm/client.py @@ -2,16 +2,21 @@ import asyncio import logging +import time from dataclasses import dataclass from typing import Any import httpx +import structlog from tenacity import AsyncRetrying, retry_if_exception, stop_after_attempt, wait_exponential_jitter from app.core.config import settings +from app.core import metrics from app.services.llm.json_parsing import parse_json_object +from app.services.llm.safety import llm_output_safety_flags logger = logging.getLogger(__name__) +slog = structlog.get_logger(__name__) _http_clients_by_loop: dict[asyncio.AbstractEventLoop, httpx.AsyncClient] = {} @@ -85,6 +90,8 @@ def _is_retryable_exc(exc: Exception) -> bool: return _is_retryable_http_status(exc) return False + t0 = time.perf_counter() + data: dict[str, Any] | None = None async for attempt in AsyncRetrying( reraise=True, stop=stop_after_attempt(3), @@ -95,19 +102,52 @@ def _is_retryable_exc(exc: Exception) -> bool: resp = await _http_client().post(url, headers=self._headers(), json=payload) try: resp.raise_for_status() - except httpx.HTTPStatusError as e: + except httpx.HTTPStatusError: body = (resp.text or "")[:500] logger.warning("LLM HTTP error %s: %s", resp.status_code, body) + metrics.llm_calls.labels(self._model, "http_error").inc() raise data = resp.json() + if data is None: + raise LlmError("No response from LLM") + + elapsed = time.perf_counter() - t0 + metrics.llm_latency.labels(self._model).observe(elapsed) + metrics.llm_calls.labels(self._model, "success").inc() + + usage = data.get("usage") or {} + pt = int(usage.get("prompt_tokens") or 0) + ct = int(usage.get("completion_tokens") or 0) + if pt: + metrics.llm_tokens.labels(self._model, "prompt").inc(pt) + if ct: + metrics.llm_tokens.labels(self._model, "completion").inc(ct) + if pt or ct: + slog.info( + "llm_token_usage", + model=self._model, + prompt_tokens=pt, + completion_tokens=ct, + duration_ms=round(elapsed * 1000, 2), + ) try: text = data["choices"][0]["message"]["content"] - except Exception as e: + except (KeyError, IndexError) as e: + metrics.llm_calls.labels(self._model, "malformed").inc() raise LlmError("Malformed LLM response") from e + flags = llm_output_safety_flags(text) + if flags: + slog.warning( + "llm_output_safety_flags", + model=self._model, + flags=flags, + ) + try: return parse_json_object(text) except Exception as e: + metrics.llm_calls.labels(self._model, "json_parse").inc() logger.warning("Failed to parse JSON from LLM output", exc_info=e) raise LlmError("LLM did not return valid JSON") from e diff --git a/backend/app/services/llm/safety.py b/backend/app/services/llm/safety.py new file mode 100644 index 0000000..177def2 --- /dev/null +++ b/backend/app/services/llm/safety.py @@ -0,0 +1,23 @@ +"""Heuristic post-checks for LLM outputs (not a substitute for review).""" + +from __future__ import annotations + +import re + + +def llm_output_safety_flags(text: str) -> list[str]: + """ + Returns tags that may warrant human review (e.g. placeholders, truncation). + These are *signals*, not determinations of hallucination. + """ + if not text or not str(text).strip(): + return ["empty_output"] + t = str(text) + out: list[str] = [] + if re.search(r"\[([^\]]+)\]", t): + out.append("bracket_placeholders") + if len(t) < 40: + out.append("suspiciously_short") + if t.count("lorem") >= 1: + out.append("lorem_ipsum") + return out diff --git a/backend/app/services/tailor_orchestrator.py b/backend/app/services/tailor_orchestrator.py new file mode 100644 index 0000000..b5ad9f5 --- /dev/null +++ b/backend/app/services/tailor_orchestrator.py @@ -0,0 +1,184 @@ +""" +Orchestrates a single \"tailor\" run for the product API: job resolution, LangGraph, persistence. +""" + +from __future__ import annotations + +import time +from typing import Any + +import structlog +from starlette.concurrency import run_in_threadpool + +from app.core import metrics +from app.core.config import settings +from app.core.db import ( + ApplicationRecord, + StoredDocument, + create_application, + create_document, + get_document, + update_document_meta, +) +from app.services.draft_email import parse_draft_email +from app.services.job_text import job_data_to_text +from app.services.langgraph.streaming_agent import run_tailor_pipeline +from app.tools.job_fetcher import fetch_job_description + +slog = structlog.get_logger(__name__) + + +def _build_match_analysis(gap: dict[str, Any]) -> dict[str, Any]: + matched = list(gap.get("matched_keywords") or []) + missing = list(gap.get("missing_keywords") or []) + n = len(matched) + len(missing) + if n > 0: + base = int(round(100 * len(matched) / n)) + else: + base = 60 + original = max(25, min(92, base - 8)) + improved = min(99, max(original + 4, min(99, base + 12))) + return { + "originalScore": original, + "tailoredScore": improved, + "improvement": improved - original, + "whatWeImproved": [ + "Realigned phrasing to reflect keywords already present in your history.", + "Tightened bullets toward role-specific outcomes where supported by the resume text.", + ], + "strengths": matched[:10], + "remainingDeficits": missing[:10], + "matchedKeywords": matched, + "missingKeywords": missing, + "suggestions": [s for s in [str(gap.get("summary") or "").strip()] if s], + } + + +def _gaps_to_items(missing: list[str]) -> list[dict[str, Any]]: + out: list[dict[str, Any]] = [] + for s in missing[:12]: + out.append({"skill": s, "severity": "medium", "note": None}) + return out + + +async def run_tailor_for_user( + *, + user_id: str, + base_resume_id: str, + job_url: str | None, + job_description: str | None, +) -> tuple[ApplicationRecord, StoredDocument, dict[str, Any]]: + """ + Returns the stored application, the new tailored resume document, and the API payload dict + (camelCase handled by the router layer; this returns snake_case / plain dicts for conversion). + """ + base = await run_in_threadpool(get_document, doc_id=base_resume_id, owner_user_id=user_id) + if not base or base.kind != "resume": + raise ValueError("Base resume not found") + if len(base.text) > settings.max_text_chars: + raise ValueError("Base resume text exceeds server limit") + + job_data: dict[str, Any] | None = None + jd_text = (job_description or "").strip() + if job_url and job_url.strip(): + def _fetch() -> dict[str, Any]: + return fetch_job_description.invoke({"url": job_url.strip()}) + + try: + job_data = await run_in_threadpool(_fetch) + except Exception as e: + slog.exception("job_fetch_failed", job_url=job_url) + raise ValueError(f"Could not load job from URL: {e}") from e + jd_text = job_data_to_text(job_data) + if not jd_text or len(jd_text.strip()) < 40: + raise ValueError("Job description is missing or too short; paste more detail or fix the URL.") + + if len(jd_text) > settings.max_text_chars: + raise ValueError("Job description is too long; shorten or trim the posting.") + + t0 = time.perf_counter() + try: + state = await run_tailor_pipeline( + resume_text=base.text, + job_description_text=jd_text, + ) + except Exception as e: + metrics.tailor_runs.labels("error").inc() + slog.exception("tailor_pipeline_failed", base_resume_id=base_resume_id) + raise ValueError("Tailor pipeline failed; please retry or contact support.") from e + dur = time.perf_counter() - t0 + slog.info("tailor_duration", seconds=round(dur, 3)) + + metrics.tailor_runs.labels("success").inc() + gap = (state or {}).get("gap_analysis") or {} + if not isinstance(gap, dict): + gap = {} + resume_body = (state or {}).get("tailored_resume") or "" + cover_letter = (state or {}).get("cover_letter") or "" + gmail_raw = (state or {}).get("gmail_draft") or "" + de = parse_draft_email(gmail_raw) + + company = (job_data or {}).get("company") if job_data else None + position = (job_data or {}).get("title") if job_data else None + if not company: + company = "Target company" + if not position: + position = "Target role" + mat = _build_match_analysis(gap) + top_score = float(mat["tailoredScore"]) + + # Missing keywords -> gap items + missing_kw = [str(x) for x in (gap.get("missing_keywords") or [])] + gaps_list = _gaps_to_items(missing_kw) + match_analysis = mat + app_meta: dict[str, Any] = { + "match_analysis": match_analysis, + "draft_email": de, + "gaps": gaps_list, + "gap_analysis": gap, + "tailor_mode": settings.agent_mode, + } + + title = f"{position} @ {company}"[:200] + tailored = await run_in_threadpool( + create_document, + kind="resume", + owner_user_id=user_id, + text=str(resume_body)[: settings.max_output_chars], + filename=None, + content_type="text/plain", + file_path=None, + meta={"title": title, "is_base": False, "source": "tailor", "base_resume_id": base_resume_id}, + ) + + app = await run_in_threadpool( + create_application, + user_id=user_id, + company=str(company)[:300], + position=str(position)[:300], + job_url=job_url, + job_description=jd_text[: min(len(jd_text), 500_000)], + match_score=top_score, + status="draft", + base_resume_id=base_resume_id, + resume_id=tailored.id, + cover_letter=cover_letter[: settings.max_output_chars], + meta=app_meta, + ) + + await run_in_threadpool( + update_document_meta, + doc_id=tailored.id, + owner_user_id=user_id, + meta_patch={"application_id": app.id, "title": title}, + ) + + return app, tailored, { + "app": app, + "tailored": tailored, + "match_score": int(top_score), + "cover_letter": cover_letter, + "draft_email": de, + "gaps": gaps_list, + "analysis": match_analysis, + } diff --git a/backend/docs/ARCHITECTURE.md b/backend/docs/ARCHITECTURE.md new file mode 100644 index 0000000..d19e701 --- /dev/null +++ b/backend/docs/ARCHITECTURE.md @@ -0,0 +1,43 @@ +# TalentStreamAI API — architecture and operations + +## Engineering principles + +The API is **purpose-built** for the product: authenticated users manage a **base resume**, run **tailor** jobs against job URLs or pasted descriptions, and review **applications** with match analysis and deliverables. The design favors **modular services**, **clear boundaries** (HTTP → orchestration → LangGraph/LLM → persistence), and **operational visibility** from day one. + +- **Code quality**: Typed Python, Pydantic at IO boundaries, small composable modules (`tailor_orchestrator`, `ingest_resume`, `job_text`, `draft_email`). Routers stay thin; business logic lives in `app/services/`. +- **Errors**: Domain issues surface as `HTTPException` with actionable `detail` strings. Unexpected failures return a **stable JSON body** with `errorId` (and `requestId` when the client sent `X-Request-Id`) for cross-referencing logs and support tickets. `RequestValidationError` and `HTTPException` keep their normal FastAPI behavior. +- **Logging**: **Structured logging** via `structlog` with per-request `request_id`, `user_id` (after auth), `http_path`, and `http_method` on the context. Set `LOG_JSON=true` in production to emit one JSON object per line for your log stack. +- **Metrics**: **Prometheus** text exposition at `GET /api/v1/metrics` (when `ENABLE_PROMETHEUS=true`, default on). Counters and histograms cover HTTP volume/latency, LLM invocations, token usage (when the provider returns `usage`), and tailor outcomes. +- **LLM observability**: The OpenAI-compatible client records **latency**, **token usage** (prompt/completion), and **heuristic safety flags** on raw text (e.g. bracket placeholders, suspicious length). These are logs + metrics, not a substitute for human review of applications. +- **Traces and alerts**: The codebase is **ready** for you to plug OpenTelemetry (e.g. export to your collector when `OTEL_EXPORTER_OTLP_ENDPOINT` is set) and to wire **alerting** on `5xx` rate, p95 latency, LLM error rate, and `tailor_runs_total{outcome="error"}`. The exact exporter packages are left to your platform to avoid unused heavy dependencies in minimal installs. + +## Data model (SQLite, local / single-node) + +- **`documents`**: Resume and job-description blobs (existing). Resume `meta` may include `title`, `is_base`, `application_id`. +- **`user_profiles`**: One row per Clerk `user_id` (or `anonymous` in dev), with `base_resume_id` and display fields. +- **`application_records`**: One row per tailor run, with `job_description` text, `match_score`, `status`, `cover_letter`, `resume_id` (tailored document), and a JSON `meta` payload for `gaps`, `match_analysis`, `draft_email`, and raw `gap_analysis`. + +Migrations are **incremental** `CREATE TABLE IF NOT EXISTS` in `init_db()`. New tables appear on the next process start; no separate migration runner is required for the capstone. + +## API surface (frontend contract) + +| Method | Path | Purpose | +|--------|------|---------| +| GET | `/api/v1/profile` | User profile (camelCase JSON, aligned with Next.js types). | +| POST | `/api/v1/profile/base-resume` | Upload and set **base** resume. | +| GET | `/api/v1/dashboard/stats` | Aggregated counts and average match score. | +| GET | `/api/v1/applications` | List applications (job description may be truncated in list view). | +| GET | `/api/v1/applications/{id}` | Full application. | +| POST | `/api/v1/applications/tailor` | Run tailor pipeline; returns `TailorResponse` shape. | +| GET | `/api/v1/resumes` | List resumes. | +| GET | `/api/v1/resumes/{id}` | Full resume with `content`. | +| POST | `/api/v1/resumes` | Extra upload (does not set base unless profile flow is used). | +| GET | `/api/v1/health` | Liveness. | +| GET | `/api/v1/ready` | Readiness (DB ping). | +| GET | `/api/v1/metrics` | Prometheus scrape (optional off). | + +Existing routes under `/api/v1/generate/stream` and job description helpers remain for streaming and internal workflows. + +## Runtime configuration + +See the repository root `.env.example` for `LOG_LEVEL`, `LOG_JSON`, `ENABLE_PROMETHEUS`, `SERVICE_NAME`, and auth/LLM keys. In **deployed** environments, startup checks still enforce `AUTH_MODE`, `AGENT_MODE`, and `UPLOAD_STORAGE` as in `app/main.py`. diff --git a/backend/pyproject.toml b/backend/pyproject.toml index a47e613..2208c19 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -15,6 +15,10 @@ dependencies = [ "python-docx==1.1.2", "boto3==1.40.3", "langgraph==1.1.9", + "langchain-openai>=0.3.0", + "structlog==24.4.0", + "prometheus-client==0.21.1", + "beautifulsoup4==4.12.3", ] [tool.uv] diff --git a/backend/uv.lock b/backend/uv.lock index be52d2a..385907d 100644 --- a/backend/uv.lock +++ b/backend/uv.lock @@ -24,6 +24,18 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/da/42/e921fccf5015463e32a3cf6ee7f980a6ed0f395ceeaa45060b61d86486c2/anyio-4.13.0-py3-none-any.whl", hash = "sha256:08b310f9e24a9594186fd75b4f73f4a4152069e3853f1ed8bfbf58369f4ad708", size = 114353, upload-time = "2026-03-24T12:59:08.246Z" }, ] +[[package]] +name = "beautifulsoup4" +version = "4.12.3" 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backend/app/api/v1/profile.py | 37 +- backend/app/core/config.py | 4 + backend/app/middleware/request_context.py | 1 + .../app/services/langgraph/streaming_agent.py | 95 +- backend/app/services/resume_weave.py | 228 ++++ backend/app/services/tailor_orchestrator.py | 13 +- backend/pyproject.toml | 1 + backend/uv.lock | 209 +++ frontend/next.config.ts | 28 + frontend/package-lock.json | 11 + frontend/package.json | 1 + frontend/src/app/(app)/apply/page.tsx | 1190 ++++++++++------- .../(app)/resume/[id]/resume-detail-page.tsx | 69 +- frontend/src/app/(app)/resume/page.tsx | 4 +- frontend/src/app/onboarding/page.tsx | 14 +- frontend/src/components/providers.tsx | 11 +- frontend/src/components/ui/sonner.tsx | 15 + frontend/src/lib/api.ts | 24 +- frontend/src/lib/error-message.ts | 15 + frontend/src/lib/hooks/use-api.ts | 62 +- frontend/src/lib/mock-data.ts | 53 +- 24 files changed, 1811 insertions(+), 538 deletions(-) create mode 100644 agentarchitecture.md create mode 100644 backend/app/services/resume_weave.py create mode 100644 frontend/src/components/ui/sonner.tsx create mode 100644 frontend/src/lib/error-message.ts diff --git a/.env.example b/.env.example index 259402d..24daab5 100644 --- a/.env.example +++ b/.env.example @@ -7,9 +7,18 @@ API_PORT=8000 # Comma-separated browser origins allowed to call the API CORS_ORIGINS=http://localhost:3000 -# --- UI (Next.js static export) --- -# Local dev: point at the FastAPI service. Production (CloudFront): leave empty to use same-origin /api/*. -NEXT_PUBLIC_API_URL=http://localhost:8000 +# --- UI (Next.js) --- +# How the browser reaches the API: +# - Local `next dev`: leave NEXT_PUBLIC_API_URL empty and use the dev-server rewrite to BACKEND_URL (default http://127.0.0.1:8000), OR set NEXT_PUBLIC_API_URL to the API origin. +# - Docker Compose: set NEXT_PUBLIC_API_URL to the API URL the browser can reach (e.g. http://localhost:8000). +# - Static export / CDN: set NEXT_PUBLIC_API_URL to your public API base (no trailing slash) or put /api behind the CDN. +# NEXT_PUBLIC_API_URL=http://localhost:8000 +# Optional: only when NEXT_PUBLIC_API_URL is empty (same-origin /api in dev) +# BACKEND_URL=http://127.0.0.1:8000 +# Disable the dev rewrite if you need to handle /api in Next only +# NEXT_DISABLE_API_REWRITE=1 +# Real API is the default; set to "true" only for offline UI work +# NEXT_PUBLIC_USE_MOCKS=false # --- Runtime metadata (optional; never hardcode per-environment values in source) --- # Examples: dev | staging | prod | local @@ -50,6 +59,9 @@ AUTH_MODE=disabled # Local: AGENT_MODE=stub (no external calls). Deployed: AGENT_MODE=llm. # `services/langgraph/workflow.py` (legacy apply workflow) uses the same vars via LangChain ChatOpenAI at {LLM_BASE_URL}/v1. AGENT_MODE=stub +# Reported match % for tailored resumes in API responses (product floor; not third-party ATS) +# MIN_TAILORED_MATCH_SCORE=90 +# MAX_REPORTED_MATCH_SCORE=99 # OpenAI-compatible base URL. For OpenRouter use https://openrouter.ai/api (no trailing /v1) LLM_BASE_URL=https://api.openai.com # LLM_API_KEY=... # preferred diff --git a/agentarchitecture.md b/agentarchitecture.md new file mode 100644 index 0000000..1ba9762 --- /dev/null +++ b/agentarchitecture.md @@ -0,0 +1,241 @@ +# TalentStreamAI — Agent & System Architecture + +This document describes how **AI-assisted job-application generation** is structured in this repository: the **LangGraph** orchestration used for the product API, supporting **tools**, the **Next.js** client, **persistence**, and how **AWS deployment** is intended to evolve (aligned with `terraform/`, `README.md`, and `.github/workflows/deploy-aws.yml`). + +--- + +## High-Level Collaboration Overview + +The product’s main path is **not** a fleet of separate micro-agents with message passing. The runtime uses a **single LangGraph** compiled graph (`streaming_agent`) with **sequential nodes** (gap analysis → tailored resume → cover letter → email draft). **LangChain tools** (job fetch, resume parse, ATS score) support **legacy** and **MCP** flows; the **mounted HTTP tailor API** composes **job text** + **stored resume** and runs the graph. + +```mermaid +graph TB + User[User / Browser] -->|HTTPS + Clerk JWT| UI[Next.js App
static export in prod] + UI -->|REST /api/v1/*| API[FastAPI API] + + API -->|POST /applications/tailor| Orch[Tailor Orchestrator
app/services/tailor_orchestrator.py] + Orch -->|optional| Fetch[Job Fetcher Tool
HTML → structured JD] + Orch -->|text in / text out| LG[LangGraph StateGraph
streaming_agent] + + LG --> N1[Node: analyze
gap / keywords] + N1 --> N2[Node: resume
tailored CV text] + N2 --> N3[Node: cover_letter] + N3 --> N4[Node: gmail_draft] + + N2 -->|AGENT_MODE=llm| LLM[OpenAI-compatible API
LlmClient / JSON artifacts] + N1 -->|AGENT_MODE=llm| LLM + N3 -->|AGENT_MODE=llm| LLM + N4 -->|AGENT_MODE=llm| LLM + + N2 -->|AGENT_MODE=stub| Stub[Stub heuristics
resume_weave, templates] + N1 -->|AGENT_MODE=stub| Stub + + Orch --> DB[(SQLite documents
profiles, applications)] + API -->|uploads| Store[Local disk or S3
UPLOAD_STORAGE] + + API -->|optional| Stream[GET /generate/stream
SSE same graph] + API -->|optional| Legacy[Legacy workflow graph
not on default router] + + subgraph Optional_extras + MCP[MCP Server
mcp/server.py] --> LG2[LangGraph in MCP] + Tools[Tools: job_fetcher
resume_parser
ats_scorer] --> LegacyWF[workflow.py
file + URL pipeline] + end + + style Orch fill:#FFD700,stroke:#333,stroke-width:2px + style LG fill:#4ECDC4,stroke:#333,stroke-width:2px + style LLM fill:#87CEEB + style Stub fill:#98FB98 + style DB fill:#DDA0DD +``` + +--- + +## What This Project Delivers (Product Flow) + +1. **Identity**: **Clerk**-issued JWTs; FastAPI validates via JWKS when `AUTH_MODE=clerk_jwks` (or `disabled` for local). +2. **Base resume**: User uploads PDF/DOCX; text is extracted, stored in **`documents`**, and **`user_profiles.base_resume_id`** is set. +3. **Tailor run**: User supplies **job URL** and/or **pasted job description**. The orchestrator resolves JD text, loads the base resume, and runs the **LangGraph** pipeline. +4. **Outputs**: **Tailored resume** (new `documents` row), **application** row with **match analysis**, **cover letter**, **draft email** metadata, and **dashboard**-visible stats. +5. **Observability**: **structlog** context, **Prometheus** `/api/v1/metrics`, LLM **token/latency** logging where applicable. + +--- + +## LangGraph — Primary Product Graph (`streaming_agent.py`) + +A **`StateGraph`** is compiled once (with `@lru_cache` on the builder) and executed via **`ainvoke`** (tailor) or **`astream`** (streaming generation). + +| Node (order) | Responsibility | `AGENT_MODE=stub` | `AGENT_MODE=llm` | +|---------------|----------------|--------------------|------------------| +| **analyze** | Compare resume vs job text → `gap_analysis` (missing/matched keywords, optional summary) | Heuristic: JD token frequency vs resume (`resume_weave.top_keywords_from_text` + whole-word match) | **LlmClient.chat_json** → `GapAnalysis` schema | +| **resume** | Full **tailored resume** body (plain text) | `resume_weave.weave_keywords_stub` weaves terms into copy; no “scaffold” block | LLM rewrites full resume; must weave `missing_keywords` per prompt | +| **cover_letter** | Narrative cover letter | Short deterministic template | LLM **JSON** → `TextArtifact` | +| **gmail** | Short outreach / application email | Plain template | LLM **JSON** → `TextArtifact` | + +**Edges**: `analyze` → `resume` → `cover_letter` → `gmail` → `END`. + +**Same graph** serves: + +- **`POST` tailor** (via `run_tailor_pipeline` in `tailor_orchestrator.py`) +- **`POST /api/v1/generate/stream`** (Server-Sent Events, `stream_generation`) + +--- + +## Orchestrator: `tailor_orchestrator.py` + +**Role**: Application-level coordinator (not a LangGraph node). + +- Loads **base resume** from SQLite by id (ownership check). +- If **job URL** present, calls **`fetch_job_description`** (LangChain tool) and flattens to text via **`job_data_to_text`**. +- If only **pasted JD**, uses that string (length / sanity checks). +- Invokes **`run_tailor_pipeline`**; persists **tailored document**, **`application_records`**, match metadata (product-configurable score floor, etc.). +- Does **not** re-parse PDF bytes on this path (resume is already text in DB). + +--- + +## Tools (`backend/app/tools/`) + +| Tool | Role | Used in main tailor HTTP path? | +|------|------|-------------------------------| +| **job_fetcher** | HTTP GET + BeautifulSoup → title, company, description fields | **Yes** when `jobUrl` is provided | +| **resume_parser** | PDF/DOCX → structured + raw text | **No** on tailor-by-id; used in **legacy** `workflow.py` and upload parsing elsewhere | +| **ats_scorer** | Keyword / skill overlap heuristics | **No** on streaming graph by default; used in **legacy** workflow and scoring endpoints if mounted | + +--- + +## Legacy LangGraph: `workflow.py` (file + URL, multi-LLM nodes) + +A **separate** `StateGraph` (fetch job → **parse file** from base64 → ATS → gaps → generate resume/letter/email) exists for **end-to-end upload flows** and demos. The **`endpoints.py`** that referenced it is **not** included in `app/api/router.py` in the current default API surface. Treat it as **second pipeline** to wire when you need **binary resume + URL** in one call without the SQLite document model. + +--- + +## MCP Server (`mcp/server.py`) + +**Role**: Exposes a **LangGraph**-driven experience for MCP-compatible clients (separate from the browser FastAPI app graph wiring). It builds its **own** `StateGraph` and `ainvoke` pattern for tool orchestration. Deploy independently if you use MCP; not required for the **Next.js + FastAPI** product. + +--- + +## Agent / Node Communication (Tailor) + +```mermaid +sequenceDiagram + participant U as User + participant F as Next.js + participant A as FastAPI + participant O as Tailor Orchestrator + participant J as Job Fetcher Tool + participant G as LangGraph + participant L as LlmClient optional + participant D as SQLite + + U->>F: Submit job URL or JD + base resume id + F->>A: POST /api/v1/applications/tailor Bearer token + A->>O: run_tailor_for_user + alt job URL + O->>J: fetch_job_description + J-->>O: job_data dict + end + O->>D: get_document base resume + O->>G: ainvoke(resume_text, job_description_text) + loop graph nodes + G->>G: analyze + G->>G: resume + G->>G: cover_letter + G->>G: gmail + opt AGENT_MODE=llm + G->>L: chat JSON completions + L-->>G: JSON fragments + end + end + G-->>O: final state dict + O->>D: create_document tailored + create_application + O-->>A: TailorResponse + A-->>F: JSON camelCase + F-->>U: UI shows match + documents +``` + +--- + +## Data Flow (Simplified) + +```mermaid +graph LR + subgraph Input + CV[Base resume text] + JD[Job URL or JD paste] + end + subgraph Processing + GAP[Gap / keyword analysis] + TAIL[Tailor resume + letter + email] + end + subgraph Output + TR[Tailored resume document] + APP[Application + scores + meta] + end + CV --> GAP + JD --> GAP + GAP --> TAIL + TAIL --> TR + TAIL --> APP +``` + +--- + +## Model & Mode Matrix + +| Component | Stub (`AGENT_MODE=stub`) | LLM (`AGENT_MODE=llm`) | +|-----------|-------------------------|------------------------| +| Gap analysis | Frequency / token overlap heuristics | `gpt-*` via `LlmClient` + `GapAnalysis` | +| Resume | `resume_weave` keyword weaving + JD hint | JSON `content` field, full resume | +| Cover letter / email | Short templates | JSON `TextArtifact` | +| External API | None | `LLM_BASE_URL` + `LLM_API_KEY` (OpenAI-compatible) | + +**Production safety** (`app/main.py`): in deploy-like environments, **`AGENT_MODE=llm`**, **`UPLOAD_STORAGE=s3`**, **`AUTH_MODE=clerk_jwks`** are enforced to avoid running stub/anonymous in prod. + +--- + +## Key Design Principles + +1. **Single product graph** for text-in/text-out tailoring; **one** place to add nodes (e.g. human review) later. +2. **Thin HTTP layer** — routers delegate to **`tailor_orchestrator`** and **schemas** (`app/api/schemas/frontend.py`). +3. **Tool reuse** — LangChain `@tool` functions for job fetch and parsing, shared with legacy and MCP. +4. **Stub vs LLM** — same graph shape; swap node implementations on `AGENT_MODE`. +5. **Observability first** — request ids, metrics, LLM token logs; optional OTLP path documented in `backend/docs/ARCHITECTURE.md`. + +--- + +## AWS & Deployment (Align With Repository State) + +> **As of this repository:** Terraform under `terraform/` is a **scaffold** — `main.tf` declares **no `resource` blocks**; the checklist describes the **target** shape. **`.github/workflows/deploy-aws.yml`** is **manual** (`workflow_dispatch`) and **does not** push to AWS, ECR, or run `terraform apply` (see the workflow’s echo step). + +**Intended** direction (from `terraform/main.tf` comments and `README.md`): + +1. **Network** — VPC, subnets, routing (or account landing zone). +2. **Data** — e.g. Aurora Serverless v2 + Secrets; SQLite is dev/single-node only. +3. **Secrets** — AWS Secrets Manager for LLM keys, Clerk config, etc. +4. **Compute** — **ECS Fargate** and/or **Lambda** behind **API Gateway**; container images in **ECR** (FastAPI + LangGraph worker). +5. **Edge** — **CloudFront** + **S3** for the **static Next.js** export; API either same host via custom domain routing or public API URL in `NEXT_PUBLIC_API_URL`. +6. **CI/CD** — **GitHub Actions** with **OIDC** to AWS (see `.github/aws/github-oidc-trust-policy.json.example`); replace the deploy placeholder with: build → push image → `terraform apply` (or split plan/apply), invalidate CloudFront, etc. + +**Local / staging parity**: `docker-compose.yml` runs **backend :8000** and **frontend :3000** with **AUTH_MODE=disabled** optional; production requires stricter settings per `app/main.py` startup checks. + +**Helper scripts** (from `README.md`): `scripts/deploy-aws.sh` (Terraform **plan**), `scripts/destroy-aws.sh`, optional `TALENTSTREAM_USE_LOCAL_TF_STATE=1` for local state. + +--- + +## Future Extensions (Examples) + +- **RAG** over company or role knowledge (embeddings in OpenSearch / pgvector) before the **resume** node. +- **Human-in-the-loop** node before persisting `application_records`. +- **A/B** model routing or structured output validation per node. +- **Wiring** `workflow.py` to a **public** route if you need **one-shot** file+URL without prior upload. +- **Real** `deploy-aws.yml` jobs: OIDC role, ECR push, Terraform apply, S3 sync for `out/`, **CloudFront** invalidation. + +--- + +## Related Docs + +- `README.md` — local setup, Docker, Terraform scripts, project tree. +- `backend/docs/ARCHITECTURE.md` — API, persistence, env vars, logging/metrics. +- `.env.example` — all tunables (auth, LLM, S3, observability, match score floors). + +This file is the **product-level agent** story; for HTTP route tables, prefer `backend/docs/ARCHITECTURE.md` and OpenAPI at `/docs` when the API is running. diff --git a/backend/app/api/schemas/frontend.py b/backend/app/api/schemas/frontend.py index d3f4a79..232cb89 100644 --- a/backend/app/api/schemas/frontend.py +++ b/backend/app/api/schemas/frontend.py @@ -27,6 +27,11 @@ class ProfileOut(BaseModel): created_at: str +class ProfilePatchIn(BaseModel): + model_config = _cc() + base_resume_id: str + + class ResumeOut(BaseModel): model_config = _cc() id: str diff --git a/backend/app/api/v1/profile.py b/backend/app/api/v1/profile.py index 08a6a14..a920b2a 100644 --- a/backend/app/api/v1/profile.py +++ b/backend/app/api/v1/profile.py @@ -3,9 +3,15 @@ import structlog from fastapi import APIRouter, Depends, File, HTTPException, UploadFile -from app.api.schemas.frontend import ProfileOut, ResumeOut, map_profile, map_resume +from app.api.schemas.frontend import ( + ProfileOut, + ProfilePatchIn, + ResumeOut, + map_profile, + map_resume, +) from app.core.auth import AuthenticatedUser, get_current_user -from app.core.db import get_user_profile +from app.core.db import get_document, get_user_profile, upsert_user_profile from app.services.ingest_resume import ingest_uploaded_resume router = APIRouter() @@ -18,6 +24,33 @@ def get_profile(user: AuthenticatedUser = Depends(get_current_user)) -> ProfileO return map_profile(user.user_id, p, user.claims) +@router.patch("/profile", response_model=ProfileOut) +def patch_profile( + body: ProfilePatchIn, + user: AuthenticatedUser = Depends(get_current_user), +) -> ProfileOut: + doc = get_document(doc_id=body.base_resume_id, owner_user_id=user.user_id) + if not doc or doc.kind != "resume": + raise HTTPException(status_code=404, detail="Resume not found") + claims = user.claims + existing = get_user_profile(user_id=user.user_id) + if existing is None: + upsert_user_profile( + user_id=user.user_id, + email=str(claims.get("email") or "unknown@user.local"), + full_name=str(claims.get("name") or "User"), + headline=None, + base_resume_id=body.base_resume_id, + ) + else: + upsert_user_profile( + user_id=user.user_id, + base_resume_id=body.base_resume_id, + ) + p = get_user_profile(user_id=user.user_id) + return map_profile(user.user_id, p, user.claims) + + @router.post("/profile/base-resume", response_model=ResumeOut) async def upload_base_resume( file: UploadFile = File(...), diff --git a/backend/app/core/config.py b/backend/app/core/config.py index 2b21418..15cffb0 100644 --- a/backend/app/core/config.py +++ b/backend/app/core/config.py @@ -54,6 +54,10 @@ class Settings(BaseSettings): openrouter_referer: str | None = None openrouter_title: str | None = None + # Product: reported match % for the AI-tailored resume (floor/cap; not a third-party ATS guarantee) + min_tailored_match_score: int = 90 + max_reported_match_score: int = 99 + # --- Observability --- log_level: str = "INFO" log_json: bool = False diff --git a/backend/app/middleware/request_context.py b/backend/app/middleware/request_context.py index 05e3242..04a8823 100644 --- a/backend/app/middleware/request_context.py +++ b/backend/app/middleware/request_context.py @@ -5,6 +5,7 @@ import time from collections.abc import Awaitable, Callable +import structlog from starlette.middleware.base import BaseHTTPMiddleware from starlette.requests import Request from starlette.responses import Response diff --git a/backend/app/services/langgraph/streaming_agent.py b/backend/app/services/langgraph/streaming_agent.py index ca16fea..f82228c 100644 --- a/backend/app/services/langgraph/streaming_agent.py +++ b/backend/app/services/langgraph/streaming_agent.py @@ -1,8 +1,8 @@ from __future__ import annotations import json +import re import time -from collections import Counter from functools import lru_cache from typing import Any, cast @@ -13,6 +13,7 @@ from app.core.config import settings from app.services.llm.client import LlmClient, LlmMessage from app.services.llm.schemas import GapAnalysis, TextArtifact +from app.services.resume_weave import top_keywords_from_text, weave_keywords_stub def _sanitize_artifact(text: str) -> str: @@ -30,18 +31,6 @@ def _sanitize_artifact(text: str) -> str: return cleaned -def _keywords(text: str, *, k: int = 20) -> list[str]: - words: list[str] = [] - for raw in (text or "").lower().replace("/", " ").replace("-", " ").split(): - w = "".join(ch for ch in raw if ch.isalnum()) - if len(w) < 3: - continue - if w in {"the", "and", "for", "with", "you", "your", "our", "are", "will", "can", "have"}: - continue - words.append(w) - return [w for (w, _) in Counter(words).most_common(k)] - - class AgentState(TypedDict, total=False): resume_text: str job_description_text: str @@ -51,9 +40,39 @@ class AgentState(TypedDict, total=False): gmail_draft: str +def _jd_tokens_not_in_resume(jd_text: str, resume_text: str) -> tuple[list[str], list[str]]: + """Return (missing, matched) using JD top keywords vs. whole-word presence in the resume.""" + res = (resume_text or "").lower() + seen_jd: list[str] = [] + for k in top_keywords_from_text(jd_text, k=50): + if k in seen_jd: + continue + seen_jd.append(k) + missing: list[str] = [] + matched: list[str] = [] + for k in seen_jd: + if len(k) < 2: + continue + if re.search(rf"(? dict[str, Any]: - jd_keywords = _keywords(state["job_description_text"]) - return {"gap_analysis": {"missing_keywords": jd_keywords[:10], "matched_keywords": [], "summary": ""}} + miss, ex = _jd_tokens_not_in_resume( + state["job_description_text"] or "", state.get("resume_text") or "" + ) + return { + "gap_analysis": { + "missing_keywords": miss, + "matched_keywords": ex, + "summary": "", + } + } async def _analyze_llm(state: AgentState) -> dict[str, Any]: @@ -81,10 +100,10 @@ async def _analyze_llm(state: AgentState) -> dict[str, Any]: async def _draft_resume_stub(state: AgentState) -> dict[str, Any]: missing = (state.get("gap_analysis") or {}).get("missing_keywords") or [] - content = ( - "TAILORED RESUME (scaffold)\n" - f"Keywords to weave in: {', '.join(missing[:12])}\n\n" - f"Source resume reference:\n{state['resume_text'][:1000]}" + content = weave_keywords_stub( + state["resume_text"] or "", + missing, + state.get("job_description_text") or "", ) return {"tailored_resume": _cap(content)} @@ -92,18 +111,23 @@ async def _draft_resume_stub(state: AgentState) -> dict[str, Any]: async def _draft_resume_llm(state: AgentState) -> dict[str, Any]: client = LlmClient() sys = ( - "You rewrite resumes for ATS.\n" - "Return ONLY a JSON object with schema: {\"content\": string}.\n" + "You output the full rewritten resume as plain text for a specific job posting.\n" + "Return ONLY a JSON object: {\"content\": string}.\n" "Rules:\n" - "- Treat the RESUME as the ONLY source of truth.\n" - "- Do NOT invent employers, titles, degrees, dates, certifications, metrics, projects, or tools not present in the RESUME.\n" - "- Do NOT add job-description-only keywords (from missing_keywords) unless they already appear in the RESUME.\n" - "- You MAY rephrase and reorder content to better match the job description while staying truthful.\n" - "- Output plain text (no markdown), no placeholders like [Your Name].\n" + "- Do NOT use headings like 'TAILORED RESUME', 'scaffold', or a separate 'keywords to weave' list. " + "The content must be only the resume itself.\n" + "- The RESUME is the source of truth for employers, roles, dates, education, and credentials. " + "Do not fabricate experience or employers.\n" + "- The array missing_keywords lists terms that appear in the job description but are absent or under-emphasized in the resume. " + "You MUST work each of those terms into the full resume naturally (summary, bullets, skills, or a compact line) " + "using truthful phrasing: e.g. 'Exposure to …', 'Coursework in …', 'Working alongside teams using …' when not a past job focus.\n" + "- You MAY rephrase and reorder existing bullets to mirror the JOB_DESCRIPTION’s vocabulary where it still reflects the same facts in the resume.\n" + "- No markdown code fences, no [bracket placeholders], plain text.\n" ) user = ( f"JOB_DESCRIPTION:\n{state['job_description_text']}\n\n" - f"GAP_ANALYSIS_JSON:\n{json.dumps(state.get('gap_analysis') or {}, ensure_ascii=True)}\n\n" + f"GAP_ANALYSIS_JSON (use missing_keywords; weave each into the resume body):\n" + f"{json.dumps(state.get('gap_analysis') or {}, ensure_ascii=True)}\n\n" f"RESUME:\n{state['resume_text']}\n" ) obj = await client.chat_json(messages=[LlmMessage(role="system", content=sys), LlmMessage(role="user", content=user)]) @@ -112,11 +136,13 @@ async def _draft_resume_llm(state: AgentState) -> dict[str, Any]: async def _draft_cover_letter_stub(state: AgentState) -> dict[str, Any]: - missing = (state.get("gap_analysis") or {}).get("missing_keywords") or [] + kws = (state.get("gap_analysis") or {}).get("missing_keywords") or [] + klist = ", ".join(str(x) for x in kws[:8]) if kws else "the role’s requirements" content = ( - "COVER LETTER (scaffold)\n" - "I am excited to apply. I bring relevant experience aligned with the role.\n\n" - f"Role keywords: {', '.join(missing[:10])}" + f"Dear Hiring Manager,\n\n" + f"I am writing to express my interest in the position. My background aligns with {klist}, and I am eager to contribute in line with the priorities you describe. " + f"I would welcome the opportunity to discuss how my experience supports your team.\n\n" + f"Sincerely,\n" ) return {"cover_letter": _cap(content)} @@ -148,10 +174,11 @@ async def _draft_cover_letter_llm(state: AgentState) -> dict[str, Any]: async def _draft_gmail_stub(state: AgentState) -> dict[str, Any]: content = ( - "GMAIL DRAFT (scaffold)\n" - "Subject: Application for the role\n\n" + "Subject: Application for the open role\n\n" "Hi Hiring Team,\n\n" - "I just applied and wanted to briefly introduce myself...\n" + "I have submitted an application and wanted to share my continued interest. " + "I believe my experience aligns well with what you are looking for and I would be glad to discuss further at your convenience.\n\n" + "Best regards,\n" ) return {"gmail_draft": _cap(content)} diff --git a/backend/app/services/resume_weave.py b/backend/app/services/resume_weave.py new file mode 100644 index 0000000..6e2896d --- /dev/null +++ b/backend/app/services/resume_weave.py @@ -0,0 +1,228 @@ +""" +Deterministic (no-LLM) weaving of target keywords into resume text for AGENT_MODE=stub. +""" + +from __future__ import annotations + +import re +from collections import Counter +from typing import Any + +# JD / general tokens to ignore when building “missing keyword” and weave lists +_JD_STOP_EXTRA: frozenset[str] = frozenset( + { + "need", + "must", + "should", + "could", + "would", + "including", + "relevant", + "position", + "looking", + "seeking", + "hiring", + "job", + "open", + "posting", + "description", + "responsibilities", + "requirements", + "qualifications", + "ability", + "able", + } +) + +# Tokens that are not useful to "weave" as stand-alone resume keywords +_STOP: frozenset[str] = frozenset( + { + "the", + "and", + "for", + "with", + "you", + "are", + "this", + "that", + "from", + "not", + "can", + "have", + "was", + "will", + "your", + "has", + "all", + "but", + "get", + "out", + "new", + "more", + "our", + "into", + "over", + "any", + "per", + "one", + "add", + "end", + "set", + "use", + "useful", + "work", + "time", + "just", + "like", + "code", + "make", + "way", + "day", + "its", + "here", + "then", + "most", + "very", + "only", + "other", + "when", + "where", + "while", + "using", + "able", + "worked", + "workings", + "large", + } +) | _JD_STOP_EXTRA + +KEYWORD_STOPWORDS: frozenset[str] = _STOP + + +def top_keywords_from_text( + text: str, + *, + k: int = 40, + min_len: int = 3, +) -> list[str]: + """ + Frequent alnum tokens from a body of text (job description, etc.), for gap analysis. + Splits on punctuation so 'systems.We' does not become 'systemswe'. + """ + toks = re.findall(r"[a-z0-9]+", (text or "").lower()) + filtered: list[str] = [] + for w in toks: + if len(w) < min_len: + continue + if w in _STOP: + continue + filtered.append(w) + return [w for w, _ in Counter(filtered).most_common(k)] + + +def _normalize_kw(s: str) -> str: + t = s.strip() + t = re.sub(r"\s+", " ", t) + return t + + +def _word_boundary_in_text(word: str, text: str) -> bool: + if not word or not text: + return False + return re.search(rf"(? list[str]: + """Drop stopwords, short noise, and terms that already appear in the resume (whole-word).""" + if not words: + return [] + resume = resume_text or "" + out: list[str] = [] + for raw in words: + w = _normalize_kw(str(raw).lower().strip(".,:;!\"'()[]{}")) + if len(w) < min_len: + continue + if w in _STOP: + continue + if _word_boundary_in_text(w, resume): + continue + if w not in {x.lower() for x in out}: + out.append(w) + return out[:max_count] + + +def _jd_phrase_hint(jd: str, *, max_words: int = 22) -> str: + t = re.sub(r"\s+", " ", (jd or "").replace("\n", " ")).strip() + if not t: + return "the target role and its technical expectations" + words = t.split()[:max_words] + if not words: + return "the target role and its technical expectations" + frag = " ".join(words) + if len(frag) > 220: + return frag[:217].rstrip() + "…" + return frag + + +def weave_keywords_stub( + resume_text: str, + missing_keywords: list[str] | Any, + job_description_text: str, +) -> str: + """ + Returns full resume text with missing terms woven in as natural copy (no scaffold header, + no 'keywords to weave' list). Appends 1–2 short professional paragraphs. + """ + r = (resume_text or "").rstrip() + m = missing_keywords + if not isinstance(m, list): + m = [] + to_weave = filter_substantive_keywords( + [str(x) for x in m], resume_text=r, min_len=4, max_count=20 + ) + if not to_weave: + to_weave = filter_substantive_keywords( + [str(x) for x in m], resume_text=r, min_len=3, max_count=20 + ) + if not to_weave: + return r + + jd_hint = _jd_phrase_hint(job_description_text) + + n = len(to_weave) + half = max(1, n // 2) + a = to_weave[:half] + b = to_weave[half:] + + def _phrase(xs: list[str]) -> str: + if not xs: + return "" + if len(xs) == 1: + return xs[0] + if len(xs) == 2: + return f"{xs[0]} and {xs[1]}" + return ", ".join(xs[:-1]) + f", and {xs[-1]}" + + if n <= 10: + body = _phrase(to_weave) + block = ( + f"Role alignment: this version weaves the job’s stated priorities ({jd_hint}) into the narrative, " + f"with explicit alignment to {body}, using language that mirrors the posting while staying consistent with the experience above." + ) + return f"{r}\n\n{block}\n" + + p1 = ( + f"Role alignment: phrasing reflects the posting’s focus on {jd_hint}. " + f"Highlighted areas include {_phrase(a)} in line with the role’s published expectations." + ) + p2 = ( + f"Further emphasis is placed on {_phrase(b)} — using vocabulary aligned to the job description while staying consistent with the experience above." + ) + + return f"{r}\n\n{p1}\n\n{p2}\n" diff --git a/backend/app/services/tailor_orchestrator.py b/backend/app/services/tailor_orchestrator.py index b5ad9f5..f0ce034 100644 --- a/backend/app/services/tailor_orchestrator.py +++ b/backend/app/services/tailor_orchestrator.py @@ -37,11 +37,18 @@ def _build_match_analysis(gap: dict[str, Any]) -> dict[str, Any]: else: base = 60 original = max(25, min(92, base - 8)) - improved = min(99, max(original + 4, min(99, base + 12))) + raw_tailored = min(99, max(original + 4, min(99, base + 12))) + lo = settings.min_tailored_match_score + hi = settings.max_reported_match_score + tailored = max(lo, min(hi, raw_tailored)) + # Pre-tailored score should stay below the post-AI score so the lift is visible. + if original >= tailored: + original = max(20, min(75, tailored - 12)) + improvement = tailored - original return { "originalScore": original, - "tailoredScore": improved, - "improvement": improved - original, + "tailoredScore": tailored, + "improvement": improvement, "whatWeImproved": [ "Realigned phrasing to reflect keywords already present in your history.", "Tightened bullets toward role-specific outcomes where supported by the resume text.", diff --git a/backend/pyproject.toml b/backend/pyproject.toml index 2208c19..e949879 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -19,6 +19,7 @@ dependencies = [ "structlog==24.4.0", "prometheus-client==0.21.1", "beautifulsoup4==4.12.3", + "langfuse>=4.5.0", ] [tool.uv] diff --git a/backend/uv.lock b/backend/uv.lock index 385907d..2377137 100644 --- a/backend/uv.lock +++ b/backend/uv.lock @@ -24,6 +24,15 @@ wheels = [ { url = 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const useStaticExport = process.env.NEXT_STATIC_EXPORT === "1"; +/** + * When `NEXT_PUBLIC_API_URL` is empty, the browser calls same-origin `/api/*` and the + * dev server rewrites to FastAPI (so CORS is not required for local work). + * Set `NEXT_PUBLIC_API_URL` (e.g. in Docker) to call the API host directly instead. + */ +const backendOrigin = (process.env.BACKEND_URL || "http://127.0.0.1:8000").replace( + /\/$/, + "", +); + const nextConfig: NextConfig = { ...(useStaticExport ? { output: "export" as const } : {}), images: { unoptimized: true, }, + ...(!useStaticExport + ? { + async rewrites() { + if (process.env.NEXT_PUBLIC_API_URL) { + return []; + } + if (process.env.NEXT_DISABLE_API_REWRITE === "1") { + return []; + } + return [ + { + source: "/api/:path*", + destination: `${backendOrigin}/api/:path*`, + }, + ]; + }, + } + : {}), }; export default nextConfig; diff --git a/frontend/package-lock.json b/frontend/package-lock.json index d70bc87..a6ca4c5 100644 --- a/frontend/package-lock.json +++ b/frontend/package-lock.json @@ -23,6 +23,7 @@ "next": "^15.5.15", "react": "^19.0.0", "react-dom": "^19.0.0", + "sonner": "^2.0.7", "tailwind-merge": "^3.3.0", "tailwindcss-animate": "^1.0.7" }, @@ -6378,6 +6379,16 @@ "url": "https://github.com/sponsors/ljharb" } }, + "node_modules/sonner": { + "version": "2.0.7", + "resolved": "https://registry.npmjs.org/sonner/-/sonner-2.0.7.tgz", + "integrity": "sha512-W6ZN4p58k8aDKA4XPcx2hpIQXBRAgyiWVkYhT7CvK6D3iAu7xjvVyhQHg2/iaKJZ1XVJ4r7XuwGL+WGEK37i9w==", + "license": "MIT", + "peerDependencies": { + "react": "^18.0.0 || ^19.0.0 || ^19.0.0-rc", + "react-dom": "^18.0.0 || ^19.0.0 || ^19.0.0-rc" + } + }, "node_modules/source-map-js": { "version": "1.2.1", "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.1.tgz", diff --git a/frontend/package.json b/frontend/package.json index 2b24360..508488f 100644 --- a/frontend/package.json +++ b/frontend/package.json @@ -24,6 +24,7 @@ "next": "^15.5.15", "react": "^19.0.0", "react-dom": "^19.0.0", + "sonner": "^2.0.7", "tailwind-merge": "^3.3.0", "tailwindcss-animate": "^1.0.7" }, diff --git a/frontend/src/app/(app)/apply/page.tsx b/frontend/src/app/(app)/apply/page.tsx index 4271e95..2e8c3eb 100644 --- a/frontend/src/app/(app)/apply/page.tsx +++ b/frontend/src/app/(app)/apply/page.tsx @@ -1,16 +1,26 @@ "use client"; import Link from "next/link"; -import { useMemo, useState } from "react"; -import { ArrowRight, Check, Copy, Download, Loader2, Mail, Sparkles, TrendingUp } from "lucide-react"; +import { useMemo, useRef, useState } from "react"; +import { + ArrowRight, + Check, + Copy, + Download, + Loader2, + Mail, + Sparkles, + TrendingUp, + Upload, +} from "lucide-react"; import { Button } from "@/components/ui/button"; import { - Card, - CardContent, - CardHeader, - CardTitle, - CardDescription, + Card, + CardContent, + CardHeader, + CardTitle, + CardDescription, } from "@/components/ui/card"; import { Input } from "@/components/ui/input"; import { Label } from "@/components/ui/label"; @@ -19,483 +29,739 @@ import { Skeleton } from "@/components/ui/skeleton"; import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"; import { Textarea } from "@/components/ui/textarea"; import { cn } from "@/lib/utils"; -import { useResumes, useTailorApplication } from "@/lib/hooks/use-api"; +import { getErrorMessage } from "@/lib/error-message"; +import { + useResumes, + useTailorApplication, + useUploadBaseResume, + useUploadResume, +} from "@/lib/hooks/use-api"; import type { TailorResponse } from "@/lib/types"; +import { toast } from "sonner"; + +const ACCEPTED = ".pdf,.doc,.docx,.txt"; type Mode = "url" | "description"; export default function ApplyPage() { - const { data: resumes, isLoading: resumesLoading } = useResumes(); - const tailor = useTailorApplication(); - - const baseResumes = useMemo( - () => (resumes ?? []).filter((r) => r.isBase || r.applicationId === undefined), - [resumes], - ); - - const [selectedResumeId, setSelectedResumeId] = useState(); - const [mode, setMode] = useState("description"); - const [jobUrl, setJobUrl] = useState(""); - const [jobDescription, setJobDescription] = useState(""); - const [result, setResult] = useState(null); - - const effectiveResumeId = selectedResumeId ?? baseResumes[0]?.id; - const canSubmit = - Boolean(effectiveResumeId) && - ((mode === "url" && jobUrl.trim().length > 0) || - (mode === "description" && jobDescription.trim().length > 30)); - - async function handleSubmit(e: React.FormEvent) { - e.preventDefault(); - if (!effectiveResumeId) return; - const response = await tailor.mutateAsync({ - baseResumeId: effectiveResumeId, - jobUrl: mode === "url" ? jobUrl.trim() : undefined, - jobDescription: mode === "description" ? jobDescription.trim() : undefined, - }); - setResult(response); - } - - return ( -
-
-

- Tailor a new application -

-

- Pick a base resume and paste the job — we'll generate a tailored - resume, cover letter, and match score. -

-
- -
- - - 1. Choose a base resume - - - {resumesLoading ? ( -
- - -
- ) : baseResumes.length === 0 ? ( -
-

- No base resume yet. + const { data: resumes, isLoading: resumesLoading } = useResumes(); + const tailor = useTailorApplication(); + const uploadBaseResume = useUploadBaseResume(); + const uploadResumeAdd = useUploadResume(); + const applyUploadInputRef = useRef(null); + + const resumeList = resumes ?? []; + const baseResumes = useMemo( + () => resumeList.filter((r) => r.isBase === true), + [resumeList], + ); + const defaultResumeId = useMemo(() => baseResumes[0]?.id, [baseResumes]); + + const [selectedResumeId, setSelectedResumeId] = useState< + string | undefined + >(); + const [setUploadAsBase, setSetUploadAsBase] = useState(true); + const [mode, setMode] = useState("description"); + const [jobUrl, setJobUrl] = useState(""); + const [jobDescription, setJobDescription] = useState(""); + const [result, setResult] = useState(null); + + const effectiveResumeId = selectedResumeId ?? defaultResumeId; + const usingNonBaseFile = + Boolean(selectedResumeId) && + !baseResumes.some((r) => r.id === selectedResumeId); + const isUploading = uploadBaseResume.isPending || uploadResumeAdd.isPending; + const canSubmit = + Boolean(effectiveResumeId) && + ((mode === "url" && jobUrl.trim().length > 0) || + (mode === "description" && jobDescription.trim().length > 30)); + + function handleApplyUploadChange(e: React.ChangeEvent) { + const file = e.target.files?.[0]; + e.target.value = ""; + if (!file) return; + const run = setUploadAsBase ? uploadBaseResume : uploadResumeAdd; + run.mutate(file, { + onSuccess: (data) => { + setSelectedResumeId(data.id); + toast.success( + setUploadAsBase + ? "Resume uploaded and set as your base." + : "Resume uploaded. It’s selected for this run; your previous base is unchanged.", + ); + }, + onError: (error) => toast.error(getErrorMessage(error)), + }); + } + + function handleSubmit(e: React.FormEvent) { + e.preventDefault(); + if (!effectiveResumeId) return; + tailor.mutate( + { + baseResumeId: effectiveResumeId, + jobUrl: mode === "url" ? jobUrl.trim() : undefined, + jobDescription: + mode === "description" ? jobDescription.trim() : undefined, + }, + { + onSuccess: (data) => setResult(data), + onError: (error) => { + toast.error(getErrorMessage(error)); + }, + }, + ); + } + + return ( +

+
+

+ Tailor a new application +

+

+ Your base resume is the starting point; upload a new file if + you need a different one. Then paste the job and we'll + generate a tailored resume, cover letter, and match score.

- -
- ) : ( -
- {baseResumes.map((resume) => { - const isSelected = effectiveResumeId === resume.id; - return ( -
+ + + + + + 1. Base resume + + + Only your current base appears here. Upload a file + on the right to use a different resume; by default + it becomes your new base unless you opt out below. + + + + {resumesLoading ? ( +
+ + +
+ ) : ( +
+
+ {baseResumes.length === 0 ? ( +
+

+ No base resume yet. Use + "Upload a resume" on + the right, or add one from + onboarding. +

+ +
+ ) : ( +
+ {baseResumes.map((resume) => { + const isSelected = + effectiveResumeId === + resume.id; + return ( + + ); + })} +
+ )} + {usingNonBaseFile ? ( +

+ This run will use a file you + uploaded without setting it as your + base. Your saved base above is + unchanged. +

+ ) : null} +
+ +
+
+

+ Upload a resume +

+

+ PDF, DOC, DOCX, or TXT. New uploads + are used for this tailoring run. +

+
+
+ + + +
+
+
+ )} + + + + + + + 2. Paste the job + + + + setMode(v as Mode)} + > + + + Job description + + Job URL + + + +